Biostats and epi with stata everything in one

Biostatistics and Epidemiology Using Stata: A Course Manual Gregory J Stoddard University of Utah School of Medicine Available on two websites: http://medicine.utah.edu/ccts/sdbc/stoddard_textbook.php http://www.ctspedia.org/do/view/CTSpedia/CourseMaterials see next page for citation suggestion Copyright © 2007, 2008, 2009, 2010, 2011, 2012, 2013 by Gregory J Stoddard All rights reserved The copyright owner grants permission for anyone to freely reproduced this bookfor academic and research purposes _ Source: Stoddard GJ Biostatistics and Epidemiology Using Stata: A Course Manual Salt Lake City, UT: University of Utah School of Medicine Title & Copyright Page (Accessed July 8, 2013, at http://medicine.utah.edu/ccts/sdbc/stoddard_textbook.php) Title & Copyright Page (revision Jul 2013) p Preface and Suggestions for Use and Author Contact Information Intended Audience The material is written for biomedical researchers who are not statisticians, and requires no mathematic skill beyond high school algebra Statisticians, however, will greatly benefit from it, because it contains a great number of solutions to common problems encountered in statistical consulting situations This course manual was designed to teach biostatistics and epidemiology to research fellows, faculty, and graduate students in biological fields The aim is to teach students to compute their own statistics for their research problems, rather than turn the analysis over to a biostatistician Teaching Style Teaching with PowerPoint is not effective In that format, not enough detail is provided, and it does not permit the student to go back months later to see how to solve a real research problem Teaching applied statistics with the traditional textbook formula approach is also not effective Statistics students fail to learn how to go beyond the formulas to apply statistics to real-word problems Nonstatisticians are not interested in the formulas, and they also fail to learn how to apply statistics to real-word problems Real-word problems are not as simple as textbook problems, almost always being something a bit messier than what is described in introductory statistics textbooks For statistics majors, the formula approach is very valuable, however, so this book should be used only as a supplement for that type of training This course manual intentionally contains less detail than a traditional textbook, but with much more detail than a PowerPoint presentation It is designed to be projected on the screen, with the instructor touching on the main points, rather than reading it as a lecture The students can see what is contained in the chapters, so they know where to refer back to when they have to apply that method to their own research problem later Having the students bring laptops to class with Stata installed allows them to the examples during the lecture, if they find this interesting and helpful _ Source: Stoddard GJ Biostatistics and Epidemiology Using Stata: A Course Manual Salt Lake City, UT: University of Utah School of Medicine Preface Page (Accessed November 5, 2011, at http://www.ccts.utah.edu/biostats/ ?pageId=5385) preface & suggestions for use (revision Nov 2011) p Consulting Help Sheets For the professional biostatistician, or the instructor who uses in this manual in the classroom, the material is useful for answering technical questions The chapter that contains the solution can be emailed to the client or student, with a note on what page the solution to their problem is presented The book is a compendium of solutions to common research problems, so is basically a book of “help sheets.” Statistical Sections for Grants and Manuscripts In many places, suggested wording for protocols and manuscripts is given These are suggested wordings are interchangeable, by writing in future tense for a protocol and past tense for a manuscript Feel free to cut-and-paste these suggestions into your grants and manuscripts, and then tailor the suggestion to match your study Suggested Citation It is perfectly appropriate to cite a web-based textbook, such as this one, and detailed instructions on found on the “title & copyright page.” However, please not feel you need to cite this course manual Wherever something worth citing is mentioned, I attempted to provide a citation to another published work You are welcome to cite those, instead, as published works have the status of being more authoritative About the Author Gregory J Stoddard is a professional biostatistician and Co-Director of the Study Design and Biostatistics Center (SDBC), www.ccts.utah.edu/biostats The SDBC is the biostatistics and epidemiology consulting group of the University of Utah Center for Clinical and Translational Science (CCTS) The CCTS is funded by a National Instititute of Health (NIH) Clinical and Translational Science Award (CTSA) His University home is in the Division of Epidemiology, Department of Internal Medicine, Univeristy of Utah School of Medicine He is also an Adjunct Assistant Professor in the Department of Orthopaedics, University of Utah School of Medicine He can be contacted at: Division of Epidemiology University of Utah School of Medicine 295 Chipeta Way, Room 1N455 Salt Lake City UT 84132 Phone: 801-213-3774 Fax: 801-581-3623 Email: greg.stoddard@hsc.utah.edu preface & suggestions for use (revision Nov 2011) p Biostatistics and Epidemiology Using Stata: A Course Manual Table of Contents > Section Stata: Data Management, Graphics, and Programming 1-1 Installing Stata and recovering Stata windows installing Stata 3 1-2 adding an icon to the desktop (PC Windows) run Stata to finish setup updating Stata after setup recoving Windows: load factory settings Getting data into Stata and some other basics 1 opening a Stata formatted data file: 1) clicking on file icon showing full dictory path in Windows Explorer showing file extensions in Windows Explorer opening a Stata formatted data file: 2) File icon on menu bar opening a Stata formatted data file: 3) change directory (cd) command directory list (dir) command read in Stata data file (use) command scrolling in Stata’s Results window general syntax, or structure, of Stata commands Stata help facility, help command Stata Manuals books on Stata setting file attributes in Windows (turn of Read Only) using do-files suggested do-file structure 10 increasing memory size of Stata’s workspace: set memory (set mem) command 10 importing Excel file into Stata 11 reading in a *.csv or *.txt formatted file: insheet command 11 saving a Stata formatted data file: save command 12 saving a Stata formatted data file compatable with Stata version or 9: saveold command _ Source: Stoddard GJ Biostatistics and Epidemiology Using Stata: A Course Manual [unpublished manuscript] University of Utah School of Medicine, 2010 table of contents (revision 16 May 2010) p 1-3 Cleaning data 2 3 5 6 7 9 1-4 listing data: list command block comment: /* … */ deleting variables: drop command inline comment “//” tabulation of values of variables using frequency table: tabulate (tab) command examining smallest and largest values: summarize, detail (sum) command replacing value of variable: replace command assignment “=” and logical equals “==” recoding values of a variable with generate (gen) and replace commands keeping a command from crashing the do-file: capture command, e.g., capture drop the “0 observations” result: attempting to arithmetic on a string variable describing variables: decribe command variable storage types missing value for string variable: the null string "" converting a string variable to numeric, destring command recoding values of a variable: recode command converting to all upper or lower case: upper and lower string functions renaming the variable name: rename command Merging files adding a file to bottom of file in memory: append command adding a file in rightmost columns of file in memory, one-to-one merge without matching on some variable: merge command merging files while matching on some variable such as a subject ID, match merge: merge command checking how well the matching worked: Stata’s _match variable (values to 3) non-overwrite feature of merge command (the default) non-overwrite of missing values feature of merge command (the default) updating file in memory with another file by replacing missing values only: update option updating file in memory with another file by replacing both missing and nonmissing values, update with replace: replace option checking how well the update with replaced worked: Stata’s _match variable (values to 5) 1-5 Labeling variables and values 3 adding label to a variable: label variable command adding labels to the values of a variable: label define and label values commands listing value labels: label list command suspending value labels in data browser and outputs, nolabel option removing variables labels removing value labels: label drop command table of contents (revision 16 May 2010) p removing value labels: capture label drop command displaying values and value labels 1-6 Basic graphics 1 3 3 4 5 using graphs from Stata version 7: graph7 and version commands redisplaying a graph: graph display command scatterplot: graph twoway scatter command appreviated scatterplot commands: twoway scatter and scatter commands side by side graph: by option linear regression line graph: lfit command overlaying graphs: “||” operator overlaying linear regression line on scatterplot using || operator overlaying graphs using binding notation: ( ) ( ) overlaying linear regression line on scatterplot using ( ) approach generating a variable with rounding: round function generating a mean across data rows for subgroups: by specification with egen command with mean function listing variables: list command extending a command across several lines in do-file editor: #delimit command line graph: line command requirement to sort on x variable before plotting a line graph: sort command table of descriptive statistics for a two variable crossclassification: table command smooth line graph using fractional polynomial fit: fpfit command fractional polynomial fit with covariates: fracpoly command adding title to graph: title command adding subtitle to graph: subtitle command adding axis titles to graph: ytitle and xtitle commands adding footnote to graph: note command adding more tick marks and labels to axes: ylabel and xlabel commands better labels for legend: legend command 10 list of choices for line graph line widths: graph query linewidthstyle command 10 changing connect line width of line graph: clwidth option 11 list of choices for graph scheme: graph query, schemes command 11 changing default graph scheme for current session or permanently: set scheme command 11 chaning graph scheme just for current graph: scheme option 12 basic black-and-white scheme for manuscripts: scheme(s1mono) option 13 eliminating border around graph: plotregion(style(none)) option 14 adding text to graph: text option 15 placement options for positioning text: placement option 16 adding space between x-axis title and x-axis tick labels: height(5) option in xtitle 17 changing color of connect line of line graph: clcolor option 17 turning off legend: legend(off) option 19 reading in graph data by putting data in do-file: input and end commands 19 adding error bars to graph: rcap command 20 overlaying errors bars on scatterplot to get symbol with error bars: table of contents (revision 16 May 2010) p twoway (rcap…) (scatter…) commands 21 adding white space to left and right side of graph: xlabel command 21 change tick mark labels to more descriptive labels: xlabel command 22 drop tick marks from graph while retaining labels: noticks option 23 adding horizontal or vertical reference lines: yline and xline options 24 list of choices for colors: help colorstyle command 24 list of choices for symbols: help symbolstyle command 24 changing marker symbol for scatterplot: msymbol option 24 changing color to marker symbol border line and inside fill: mlcolor and mfcolor options 1-7 1-8 1-9 1-10 1-11 Looping, collapsing, and reshaping Operators, ifs, dates, and times More graphics: popular scientific graphs Programming Stata Compilation of frequently used variable generation and modifying commands (a chapter for quick look up) 1-12 Stata results into Excel & Word 1-13 Homework problems Section Biostatistics 2-1 Describing variables, levels of measurement, and vhoice of descriptive statistics Describing a variable (distribution): with tables: frequency tables with graphs: histogram, boxplots with descriptive statistics: mean, standard deviation, etc Levels of measurement (nominal, ordinal, categorical, continuous ) How to decide what descriptive statistic to use to describe a variable in the “Table Patient Characteristics” table of an article 2-2 Logic of significance tests What a probability distribution is Logic of a significance test (same logic as a laboratory reference range) Chance, randomness, sampling variability Statistical regularity (the basis of statistical theory) Strong Law of Large Numbers (formal statement of statistical regularity) Deriving the form of statistical test (significance test) intuitively Sampling distribution p value 2-3 Choice of significance test table of contents (revision 16 May 2010) p 2-4 Comparison of two independent groups Role of p values in a Table Patients Characteristics table Confounding variables chi-square test Fisher’s exact test Asymptotic vs exact tests (parametric vs nonparametric tests) Minimum expected frequency rule for choosing between chi-square test and Fisher’s exact test Barnard’s unconditional exact test Fisher-Freeman-Halton test Wilcoxon-Mann-Whitney test Fisher-Pitman Permutation Test for Independent Samples Central Limit Theorem Levene’s test for equality of variances t test (both equal and unequal variances) Shapiro-Wilks test for normality Reporting styles Outliers Prespecification of analysis 2-5 Basics of power analysis definition of power power increases as sample size increases decision errors of significance tests [ Type I error (alpha), Type II error (beta) ] Type II error and sample size paragraph in journal article conclusions of equivalence power of a significance test effect of one- or two-sided comparison on power effect of choice of alpha on power effect of choice of minimum detectable effect size on power effect of size of assumed standard deviation (SD) on power – coming up with a SD estimate effect of sample size on power sample size and power calculations for an interval scaled outcome variable what to if you don’t know anything (no effect size or standard deviation estimates): the standard deviation units approach, Cohen’s d sample size calculation when a multiple comparison adjustment is planned overfitting switching the dependent and independent variables sample size based on precision (desired width of confidence interval) excessive power (sample size very large) two group comparison of interval scale outcome sample size paragraph in study protocol table of contents (revision 16 May 2010) p 2-6 More on levels of measurement sums of ordinal scales produce interval sacles dichotomous scales are actually interval scales can statistical tests that require interval scales be used with ordinal scales ( the ordinal-interval controversy in statistics) 2-7 Comparison of two paired groups 2-8 Multiplicity and the Comparison of 3+ Groups multiplicity multiple comparison problem p value based multiple comparison procedures: family-wise error rate (Bonferroni, Holm, Sidak, Holm-Sidak, Hochberg, Finner, Hommel, Tukey-Ciminera-Heyse) p value based multiple comparison procedures: false discovery rate (Benjamini-Hochberg procedure) alternative approaches to using multiple-comparison procedures simultaneous comparison of 3+ groups (includes one-way analysis of variance) sample size when multiple comparisons are planned 2-9 Correlation 2-10 Linear regression how linear regression controls for covariates 2-11 Logistic regression and dummy variables linear regression estimates risk difference (difference between proportions), but is criticized because it can estimate predicted probabilities outside of the 0-1 range logistic regression is designed to constrain the predicted probability between and definition of an odds ratio assessing linearity of effect dummy variables (indicator variables) 2-12 Survival analysis: Kaplan-Meier graphs, Log-rank Test, and Cox regression life tables Kaplan-Meier survival probabilies & Kaplan-Meier curves log-rank test Cox regression assessing goodness of fit with c-statistic (ROC area) interpreting the c-statistic testing proportional hazards assumption of Cox regression table of contents (revision 16 May 2010) p 2-13 2-14 2-15 2-16 2-17 2-18 2-19 Confidence intervals versus p values and trends toward significance Pearson correlation coefficient with clustered data Equivalence and noninferiority tests Validity and reliability Methods comparison studies One sample tests Homework problems Section Epidemiology 3-1 3-2 3-3 3-4 3-5 3-6 3-7 3-8 3-9 3-10 3-11 3-12 3-13 3-14 3-15 Introduction to epidemiologic thinking Sufficient/component cause theory of disease Hill’s causal criteria Logic and errors Effect measures Study designs Randomization using Excel Bias and confounding Random error and statistics Crude analysis Stratified analysis Standardization Sensitivity (bias) analysis Case-cohort study design Homework problems Section Power Analysis Chapter 4-1 Sample Size Determination and Power Analysis for Specific Applications two independent group comparison of means (independent groups t test) linear regression: comparing two groups adjusted for covariates two independent groups comparison of dichotomous outcome variable (chi-square test, Fisher’s exact test) two indendpent groups comparison of a nominal outcome variable (chi-square test and Fisher-Freeman-Halton test) two independent groups comparison of ordinal outcome variable (Wilcoxon-MannWhitney test) table of contents (revision 16 May 2010) p biomaker data In, Rao CR, Miller JP, Rao DC (eds), Handbook of Statistics 27: Epidemiology and Medical Statistics, New York, Elsevier.pp 109-147 {cited in: Ch 216} Lorenzen TJ, Anderson VL (1993) Design of Experiments: a No-Name Approach New York, Marcel Dekker {cited in: Ch 5-10, 5-22} Ludbrook J (1998) Multiple comparison procedures updated Clinical and Experimental Pharmacology and Physiology 25:1032-1037 {cited in: Ch 2-8} Lumley T, Diehr P, Emerson S, Chen L (2002) The importance of the normality assumption in large public health data sets Annu Rev Public Heath 23:151-69 {cited in: Ch 2-19} Magder LS, Hughes JP Logistic regression when the outcome is measured with uncertainty Am J Epidemiol 1997;146(2):195-203 {cited in: Ch 3-13} Makary MA, Al-Attar A, Holzmueller GC, et al (2007) Needlestick injuries among surgeons in training N Engl J Med 356(26):2693-9 {cited in: Ch 2-4} Maldonado G, Greenland S (1993) Simulation study of confounder-selection strategies Am J Epidemiol 183:923-936 {cited in: Ch 5-12, 5-23} Manning WG, Basu A, Mullahy J (2002) Modeling costs with generalized gamma regression University of Chicago manuscript available at: www.spc.uchicago.edu/prc/pdfs/mannin02.pdf {cited in: Ch 5-22} Manning WG, Basu A, Mullahy J (2003) Generalized modeling aproaches to risk adjustment of skewed outcomes data Harris School Working Paper Series 03.13 University of Chicago manuscript available at: http://harrisschool.uchicago.edu/about/publications/ working-papers/pdf/wp_03_13.pdf {cited in: Ch 5-22} Mantel N (1966) Evaluation of survival data and two new rank order statistics arising in its consideration Cancer Chem Rep 50:163-170 {cited in: Ch 2-12, 3-11, 5-7, 5-23} Mantel N (1977) Letter: Contingency tables—a reply The American Statistician 31:135 {cited in: Ch 3-11 5-17} Mantel N, Haenszel W (1959) Statistical aspects of the analysis of data from the retrospective studies of disease J National Cancer Inst 22:719-48 {cited in: Ch 3-11, 5-17} Mantha S, Roizen MF, Fleischer LA, et al (2000) Comparing methods of clinical measurement: reporting standards for Bland and Altman Analysis Anesth Analg 90:593-602 {cited in: Ch 2-17} Appendix (revision 15 Aug 2010) p 21 Matthews DE, Farewell V (1985) Using and understanding medical statistics New York, Karger {cited in: Ch 2-4, 3-10} Nawata K, Sohmiya M, Kawaguchi M, et al (2004) Increased resting metabolic rate in patients with type diabetes mellitus accompanied by advanced diabetic nephropathy Metabolism 53(11) Nov: 1395-1398 {cited in: Ch 5-21} McCarthy WF, Thompson DR (2007) The analysis of pixel intensity (myocardial signal density) data: the quantification of myocardial perfusion by imaging methods (May 2007) COBRA Preprint Series Article 23 http://biostats.bepress.com/cobra/ps/art23 {cited in: Ch 2-17} McDowell I (2006) Measuring Health: a Guide to Rating Scales and Questionnaires, 3rd ed., New York, Oxford University Press {cited in: Ch 2-6, 2-16} McDowell I, Newell C (1996) Measuring Health: a Guide to Rating Scales and Questionnaires, 2nd ed., New York, Oxford University Press {cited in: Ch 2-16, 5-14} McMahon JA, Green TJ, Skeaff CM, et al (2006) A controlled trial of homocysteine lowering and cognitive performance N Engl J Med 354(26):2764-72 {cited in: Ch 5-19} McWilliams JM, Meara E, Zslavsky AM, Ayanian JZ (2007) Use of health services by previoulsy uninsured Medicare beneficiaries N Engl J Med 357(2):143-53 {cited in: Ch 2-4} Merlo J, Berglund, G, Wirfält E, et al (2000) Self-administered questionnaire compared with a personal diary for assessment of current use of hormone therapy: an analysis of 16,060 women Am J Epidemiol 152:788–92 {cited in: Ch 2-16} Metha CR, et al (2000) Efficient Monte Carlo methods for conditional logistic regression J Am Statit Assoc 95(449):99-108 {cited in: Ch 5-6} Mehta CR, Patel NR (1995) Exact logistic regression: theory and examples Statistics in Medicine 14:2143-2160 {cited in: Ch 5-6} Merriam-Webster’s Collegiate Dictionary, 10th ed (1999) Springfield MA, Merriam-Webster, Inc {cited in: Ch 3-4} Messika-Zeitoun D, Aubry M-C, Detaint D, et al (2004) Evaluation and clinical implications of aortic valve calcification measured by electron-beam computed tomography Circulation 110:356-362 {cited in: Ch 5-1} Meyer PL (1970) Introductory Probability and Statistical Applications, 2nd ed Reading MA, Addison-Wesley Publishing Company {cited in: Ch 2-4} Nicoll CD, Pignone M (2003) Diagnostic testing & medical decision making In Tierney LM, Appendix (revision 15 Aug 2010) p 22 McPhee SJ, Papadakis MA (eds) Current Medical Diagnosis & Treatment 2003, 42nd ed Columbus OH, The McGraw-Hill Companies, pp 1667-1677 {cited in: Ch 2-2} Miettinen OS (1970) Matching and design efficiency in retrospective studies Am J Epidemiol 91:111-118 {cited in: Ch 5-17} Millard PS (1999) Review: bias may contribute to association of vasectomy with prostate cancer West J Med 171:91 {cited in: Ch 3-8} Millard SP, Yearsley JR, Lettenmaier DP (1985) Space-time correlation and its effect on methods for detecting aquatic ecological change Canadian Journal of Fisheries and Aquatic Science 42:1391-1400 Correction: (1986) 43:1680 {cited in: Ch 5-10, 5-22} Miller-Davis C, Marden S, Leidy NK (2006) The New York Heart Association Classes and functional status: what are we really measuring? Heart Lung 35(4):217-24 {cited in: Ch 2-98, 2-99} Miller RG, Moore DH, Gelinas DF, et al (2001) Phase III randomized trial of gabapentin in patients with amyotrophic lateral sclerosis Neurology 2001;56:843-848 {cited in: Ch 25} Milligan GW, Cooper MC (1985) An examination of procedures for determing the number of \ clusters in a dataset Psychometrika 50:159-179.{cited in: Ch 5-24} Mittlböck M, Schemeper M (1996) Explained variation for logistic regression Statistics in Medicine 15:1987-1997 {cited in: Ch 5-14} Monson RR (1980) Occupational Epidemiology Boca Raton, FL, CRC Press, Inc {cited in: Ch 3-6, 5-17} Mooney CZ, Duval RD (1993) Bootstrapping: A Nonparametric Approach to Statistical Inference Newbury Park, CA, Sage Publications {cited in: Ch 5-13, 5-14} Moons KG, Grobbee DE (2002) Diagnostic studies as multivariable, prediction research J Epidemiol Community Health 56(5):337-8 {cited in: Ch 5-9} Moran GJ, Krishnadasan A, Gorwitz RJ, et al (2006) Methicillin-resistant S auerus infections among patients in the emergency department NEJM 355(7):666-674 {cited in: Ch 3-6} Morrison AC, Bare LA, Chambless LE, et al (2007) Prediction of coronary heart disease risk using a genetic risk score: the atherosclerosis risk in communities study Am J Epidemiol 166(1):28-35 {cited in: Ch 5-14} Motzer RJ, Hutson TE, Tomczak P, et al (2007) Sunitinib versus interferon alfa in metastatic renal-cell carcinoma N Engl J Med 356(2):115-24 {cited in: Ch 2-13, 3-10} Appendix (revision 15 Aug 2010) p 23 Moyé LA (2008) The multiple comparison issue in health care research In, Rao CR, Miller JP, Rao DC (eds), Handbook of Statistics 27: Epidemiology and Medical Statistics, New York, Elsevier, pp.616-655 {cited in: Ch 2-8} Munger MA, Stoddard GJ, Wenner AR, et al (2008) Safety of prescribing PDE-5 inhibitors via e-medicine vs traditional medicine Mayo Clin Proc 83(8):890-896 {cited in: Ch 2-15} Munro BH (2001) Statistical Methods for Health Care Research 4th ed Philadelphia, Lippincott {cited in: Ch 2-1, 2-98, 2-99} Myers MH (1969) A Computing Procedure for a Significance Test of the Difference Between Two Survival Curves, Methodological Note No 18 in Methodoligcal Notes compiled by the End Results Sections, National Cancer Institute, National Institute of Health, Bethesda, Maryland {cited in: Ch 2-12, 3-5, 5-7, 5-23} National Heart, Lung, and Blood Institute (1998) Clinical guidelines for the identification, evaluation, and treatment of overweight and obesity in adults: the evidence report Bethesda, MD, National Heart, Lung, and Blood Institute {cited in: Ch 3-14, 5-14} Nawata K, Sohmiya M, Kawaguchi M, et al (2004) Increased resting metabolic rate in patients with type diabetes mellitus accompanied by advanced diabetic nephropathy Metabolism 53(11) Nov: 1395-1398 {cited in: Ch 5-4, 5-10, 5-11, Appendix 1} Nicoll CD, Pignone M (2003) Diagnostic testing & medical decision making In Tierney LM, McPhee SJ, Papadakis MA (eds) Current Medical Diagnosis & Treatment 2003, 42nd ed Columbus OH, The McGraw-Hill Companies, pp 1667-1677 {cited in: Ch 2-2, 215} Nunnally JC (1978) Psychometric Theory, 2nd ed., New York, McGraw-Hill Book Company {cited in: Ch 2-16, 5-14} Nunnally JC, Bernstein IH (1994) Psychometric Theory, 3rd ed New York, McGrawHill Book Company {cited in: Ch 2-6, 5-3} Oderda GM, Said Q, Evans RS, et al (2007) Opioid-related adverse drug events in surgical hospitalizations: impact on costs and length of stay Ann Pharmacother 41(3):400-6 {cited in: Ch 5-22} Oettle H, Post S, Neuhaus P, et al (2007) Adjuvant chemotherapy with gemcitabine vs observation in patients undergoing curative-intent resection of pancreatic cancer JAMA 297(3):267-277 {cited in: Ch 1-9, 5-7} Onyike CU, Crum RM, Lee HB, Lyketsos CG, Eaton WW (2003) Is obesity associated with major depression? Results from the third national health and nutrition examination survey Am J Epidemiol 158(12):1139-1153 {cited in: Ch 1-9, 2-98, 2-99, 3-14, 5-14, Appendix (revision 15 Aug 2010) p 24 5-24, 5-28} Orsini N, Bellocco R, Bottai M, Wolk A, Greenland S (2008) A tool for deterministic and probabilistic sensitivity analysis of epidemiologic studies The Stata Journal 8(1):29-48 {cited in: Ch 3-13} Quenot J-P, Teuff GL, Quantin C, et al (2005) Myocardial injury in critically ill patients: relation to increased cardiac troponin I and hospital mortality Chest 128(4):2758-2764 {cited in: Ch 5-5, 5-28, 5-29} Papi A, Canonica GW, Maestrelli P, et al (2007) Rescue use of beclomethasone and albuterol in a single inhaler for mild asthma N Engl J Med 356;20:2040-52 {cited in: Ch 2-5} Patton MQ (1978) Utilization-Focused Evaluation Beverly Hills, Calif, Sage Publications {cited in: Ch 3-4} Paul-Dauphin A, Guillemin F, Virion J-M, Briancon S (1999) Bias and precision in visual analogue scales: a randomize controlled trial Am J Epidemiol, 150(10):1117-27 {cited in: Ch 2-6} Pearce N (2004) Effect measures in prevalence studies Environmental Health Perspectives 112(10):1047-1050 {cited in: Ch 3-6} Pepe MS (2003) The Statistical Evaluation of Medical Tests for Classification and Prediction, New York, Oxford University Press, p.168-173 {cited in: Ch 3-13, 6-3, 6-4, Appendix dataset descriptions } Perkins NJ, Schisterman EF (2006) The inconsistency of “optimal” cutpoints obtained using two criteria based on teh receiver operating characteristic curve Am J Epidemiol 163(7):670-675 {cited in: Ch 5-14} Petrie A (2006) Statistics in orthopaedic papers Journal of Bone and Joint Surgery 88-B(9): 1121-1136 {cited in: Ch 2-5} Pettitt AN, Siskind V (1981) Effect of within-sample dependence on the Mann-WhitneyWilcoxon statistic Biometrika 68:437-441 {cited in: Ch 5-10, 5-22} Piaggio G, Elbourne DR, Altman DG, et al (2006) Reporting of noninferiority and equivalence randomized trials: an extension of the CONSORT Statement JAMA 295:1152-1160 Pocock SJ (1983) Clinical Trials: A Practical Approach New York, John Wiley & Sons {cited in: Ch 2-8} Pocock SJ, Clayton TC, Altman DG (2002) Survival plots of time-to-event outcomes in clinical trials: good practice and pitfall Lancet 359:1686-1689 {cited in: Ch 5-7} Appendix (revision 15 Aug 2010) p 25 Popper KR (1968) The Logic of Scientific Discovery New York, Harper and Row, pp.32-34 {cited in: Ch 3-4} Praetz P (1981) A note on the effect of autocorrelation on multiple regression statistics Australian Journal of Statistics 23:309-313 {cited in: Ch 5-10, 5-22} Prentice RL (1986) A case-cohort design for epidemiologic cohort studies and diease Prevention trials Biometrika 73:1-11 {cited in: Ch 3-14} Pronovost P, Needham D, Berenholtz S, et al (2006) An intervention to decrease catheterrelated bloodstream infections in the ICU N Engl J Med 355(26):2725-2732 {cited in: Ch 5-20} Rabe-Hesketh S, Everitt B (2003) A Handbook of Statistical Analyses using Stata 3rd ed New York, Chapman & Hall/CRC {cited in: Ch 5-15, 5-20, 5-21} Rabe-Hesketh S, Skrondal A (2005) Multilevel and Longitudinal Modeling Using Stata, College Station, Tx, Stata Press {cited in: Ch 5-20} Radlow R, Alf EF, Jr (1978) An alternative multinomial assessment of the accuracy of the χ2 test of goodness of fit Journal of the American Statistical Association 70:811-813 {cited in: Ch 2-18} Rao BLSP (1987) Asymptotic Theory of Statistical Inference New York, John Wiley {cited in: Ch 5-13, 5-14} Rassi A Jr, Rassi A, Little WC, et al (2006) Development and validation of a risk score for predicting death in Chagas’ heart disease N Engl J Med 355(8):799-808 {cited in: Ch 514} Rauscher GH, Mayne ST, Janerich DT (2000) Relation between body mass index and lung cancer risk in men and women never and former smokers Am J Epidemiol 152:506-13 {cited in: Ch 3-8, 5-8} Reboli AC, Rotstein C, Pappas PG, et al (2007) Anidulafungin versus fluconazole for invasive candidiasis N Engl J Med 356(24):2472-2482 {cited in: Ch 2-15, 2-98, 2-99, 4-4, 4-5} Reese WL (1980) Dictionary of Philosophy and Religion Atlantic Highlands, NJ: Humanities {cited in: Ch 3-4} Reichenheim ME (2004) Confidence intervals for the kappa statistic The Stata Journal 4(4):421-428 {cited in: Ch 2-16} Rice JA (1988) Mathematical Statistics and Data Analysis Pacific Grove, California, Wadsworth & Brooks/Cole {cited in: Ch 2-4} Appendix (revision 15 Aug 2010) p 26 Rockhill B, Newman B, Weinberg C (1998) Use and misuse of population attributable fractions Am J Public Health 88(1):15-19 {cited in: Ch 3-5} Rohatgi VK (1984) Statistical Inference New York, John Wiley {cited in: Ch 5-13, 5-14} Rosner B (1995) Fundamentals of Biostatistics, 4th ed Belmont CA, Duxbury Press {cited in: Ch 2-4, 2-9, 2-10, 2-15, 2-16, 3-10, 5-6, 5-17, Appendix 1} Rosner B (2006) Fundamentals of Biostatistics, 6th ed Belmont CA, Duxbury Press {cited in: Ch 2-4, 2-5, 2-8, 2-14, 4-1, 4-2} Ross S (1998) A First Course in Probability, 5th ed Upper Saddle River, NJ {cited in: Ch 2-5, 4-1} Ross S (2006) A First Course in Probability, 7th ed Upper Saddle River, NJ, Pearson Prentice Hall {cited in: Ch 2-98, 2-99, 5-22} Roth, P (1994) Missing data: A conceptual review for applied psychologists Personnel Psychology 47:537-560 {cited in: Ch 5-9} Rothman KJ (1986) Modern Epidemiology Boston, Little, Brown {cited in: Ch 3-5} Rothman KJ (2002) Epidemiology: An Introduction New York, Oxford University Press {cited in: Ch 2-4, 2-10, 3-1, 3-2, 3-3, 3-5, 3-6, 3-8, 3-9, 3-10, 3-11, 3-12, 3-14, 5-8, 5-17} Rothman KJ, Greenland S (1998) Modern Epidemiology, 2nd ed Philadelphia PA, Lippincott-Raven Publishers {cited in: Ch 2-10, 3-3, 3-4, 3-5, 3-6, 3-8, 3-11, 3-12, 3-14, 5-7, 5-12, 5-17} Rothman KJ, Greenland S, Lash TL (2008) Design Stategies to Improve Study Accuracy In Rothman KJ, Greenland S, Lash TL eds Modern Epidemiology, 3rd ed Philadelphia, PA, Lippincott Williams & Wilkins, 2008, pp 168-182 {cited in: Ch 5-17} Rothman KJ, Greenland S, Lash TL (2008) Case-control studies In Rothman KJ, Greenland S, Lash TL, Modern Epidemiology, Philadelphia, Lippincott Williams & Wilkins, 2008, pp.111-127 {cited in: Ch 3-14} Royall R (1997) Statisical Evidence: A Likelihood Paradigm, New York, Chapman & Hall/CRC {cited in: Ch 2-13} Royston P (2004) Multiple imputation of missing values The Stata Journal 4(3):227-241 {cited in: Ch 5-9} Royston P (2005a) Multiple imputation of missing values: update The Stata Journal 5(2):188- Appendix (revision 15 Aug 2010) p 27 201 {cited in: Ch 5-9} Royston P (2005b) Multiple imputation of missing values: update of ice The Stata Journal 5(4):527-536 {cited in: Ch 5-9} Royston P (2007) Multiple imputation of missing vlaues: further update of ice, with an emphasis on interval censoring The Stata Journal 7(4):445-464 {cited in: Ch 5-9} Rubin DB (1997) Estimating causal effects from large data sets using propensity scores Ann Intern Med 127(8 Pt 2):757-63 {cited in: Ch 5-27} Rumsfeld JS, Magid DJ, Plomondon ME, et al (2003) Health-related quality of life after percutaneous coronary intervention versus coronary bypass surgery in high-risk patients with medically refractory ischemia J Am Coll Cardiology 41(10):1732-1738 {cited in: Ch 2-15} Rutjes AW, Reitsma JB, Coomarasamy A, et al (2007) Evaluation of diagnostic tests when there is no gold standard A review of methods Health Technol Assess 11(50):iii, ix-51 {cited in: Ch 6-3} Sachs GS, Nierenberg AA, Calabrese JR, et al (2007) Effectiveness of adjunctive antidepressant treatment for bipolar depression N Engl J Med 356(17):1711-1722 {cited in: Ch 2-1} Sankoh AJ, Huque MF, Dubey SD (1997) Some comments on frequently used multiple endpoint adjustment methods in clinical trials Statistics in Medicine 16:2529-2542 {cited in: Ch 2-8} Sarle WS (1997) Measurement theory: frequently asked questions Version 3, Sep 14 URL: ftp://ftp.sas.com/pub/neural/measurement.html{cited in: Ch 2-6, 5-3} Savitz DA, Cai J, van Wijngaarden E, et al (2000) Case-cohort analysis of brain cancer and leukemia in electric utility workers using a refined magnetic field job-exposure matrix American Journal of Industrial Medicine 38:417-425 {cited in: Ch 3-14} Scheffé H (1959) The Analysis of Variance New York, John Wiley and Sons {cited in: Ch 510, 5-22} Schnonlau M (2006) Stata software package, hotdeckvar.pkg, for hotdeck imputation http://www.schonlau.net/stata/.{cited in: Ch 5-9} Schroerlucke S, Bertrand S, Clapp J, et al (2009) Failure of orthofix eight-plate for the treatment of blount disease J Pediatr Orthop 29(1):57-60 {cited in: Ch 5-6} Schuirmann DJ (1987) A comparison of the two one-sided tests procedure and the power approach for assessing the equivalence of average bioavailability J of Pharmaokin Appendix (revision 15 Aug 2010) p 28 Biopharm 15:657-680 {cited in: Ch 2-15} Scott IU, VanVeldhuisen PC, Oden NL, et al (2010) Baseline predictors of visual acuity and retinal thickness outcomes in pateints with retinal vein occlusion: standard care versus corticosteriod for retinal vein occlusion study report 10 Ophthalmology (in press) {cited in: Ch 2-8} Self SG, Prentice RL (1988) Asymptotic distribution theory and efficiency results for casecohort studies Annals of Statistics 16:64-81 {cited in: Ch 3-14} Selvin S (2004) Statistical Analysis of Epidemiologic Data 3rd ed New York, Oxford University Press {cited in: Ch 3-10, 5-6} Senn S (2007) Statistical Issues in Drug Development, 2nd ed Hoboken NJ, John Wiley & Sons {cited in: Ch 5-16} Senn S, Stevens L, Chaturvedi N (2000) Tutorial in biostatistics: repeated measures in clinical trials: simple strategies for analysis using summary measures Statist Med 19:861-877 {cited in: Ch 5-15} Shah BR, Laupacis A, Hux JE, Austin PC (2005) Propensity score methods gave similar results to traditional regression modeling in observational studies: a systematic review J Clin Epidemiol 58(6):550-9 {cited in: Ch 5-27} Shannon WD (2008) Cluster analysis In Rao CR, Miller JP, Rao DC (2008) Handbook of Statistics 27: Epidemiology and Medical Statistics New York, Elseiver, pp.342-366 {cited in: Ch 5-24} Shaw AD, Stafford-Smith M, White WD, et al (2008) The effect of aprotinin on outcome after coronary-artery bypass grafting N Engl J Med 2008;358:784-93 {cited in: Ch 5-7} Shrout PE, Fleiss JL Intraclass correlations: uses in assessing rater reliability Psychological Bulletin 1979;86(2):420-428 {cited in: Ch 2-16, 5-20} Siegel S, Castellan NJ (1988) Nonparametric Statistics for the Behavioral Sciences 2nd ed New York, McGraw-Hill {cited in: Ch 2-3, 2-4, 2-7, 2-8, 2-18, 5-17, 6-2, 6-3} Simes RJ (1986) An improved Bonferroni procedure for multiple tests of significance Biometrika 73:751-754 {cited in: Ch 2-8} Simon, S (1999) A simple approach for randomisation [Electronic Rapid Response] 17 Sep 1999 Response to Altman DG, Bland JM Statistics notes: How to randomise BMJ 319:703-704 {cited in: Ch 3-7} Smith PG, Day NE (1981) Matching and confounding in the design and analysis of epidemiological case-control studies In: Blithell JF, Coppi R, eds Perspectives in Medical Appendix (revision 15 Aug 2010) p 29 Statistics New York, Academic Press {cited in: Ch 5-17} Smith D, Eggen M, St Andre R (1997) A Transition to Advanced Mathematics, 4th ed., Pacific Grove, California, Brooks/Cole Publishing Company {cited in: Ch 2-5, 2-15} Smits M, Dippel DWJ, Steyerberg EW, et al (2007) Predicting intracranial traumatic findings in computed tomography in patients with minor head injury: the CHIP prediction rule Ann Intern Med 146:397-305 {cited in: Ch 5-14} Snedecor GW, Cochran WG (1980) Statistical Methods, 7th Ed Ames, Iowa, The Iowa State University Press {cited in: Ch 2-8} Stanojevic S, Wade A, Stocks J, et al (2008) Reference ranges for spirometry across all ages: a new approach Am J Respir Crit Care Med 177;253-260 {cited in: Ch 2-10} StataCorp (2003) Stata Statistical Software: Release 8.0 College Station, TX, Stata Corportion {cited in: Ch 3-11, 3-12} StataCorp (2007) Stata Base Reference Manual, Vol (I-P) Release 10 College Station, TX, Stata Press {cited in: Ch 2-16} StataCorp (2005) Stata Multivariate Statistics Reference Manual Release College Station, TX, StataCorp LP {cited in: Ch 5-24} StataCorp (2007) Stata Multivariate Statistics Reference Manual Release 10 College Station, TX, StataCorp LP {cited in: Ch 5-24} StatXact for Windows: Statistical Software for Exact Nonparametric Inference User Manual (2001) Cambridge MA, Cytel Software Corporation {cited in: Ch 2-3} StatXact® Version with Cytel StudioTM: Statistical Software for Exact Nonparametric Inference User Manual Cambridge, Massachusetts, Cytel Software Corporation {cited in: Ch 215} Steyerberg EW (2009) Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating New York, Springer {cited in: Ch 2-4, 2-5, 5-1, 5-9, 5-12, 5-13, 5-14, 5-27} Steyerberg EW, Eijkemans MJC, Harell Jr FE, Habbema JDK (2000) Prognostic modeling with logistic regression analysis: a comparison of selection and estimation methods in small data sets Statist Med 19:1059-1079 {cited in: Ch 5-14} Steyerberg EQ, Harrell FE, Borsboom GJJM, et al (2001) Internal validation of predictive models: efficiency of some procedures for logistic regression analysis J Clin Epidemiol 54:774-781 {cited in: Ch 5-14} Appendix (revision 15 Aug 2010) p 30 Stoddard GJ, Ring WH (1993) How to evaluate study methodology in published clinical research J Intravenous Nursing 16(2):110-117 {cited in: Ch 2-2, 2-4, 2-5} Streiner DL, Norman GR (1995) Health Measurement Scales: A Practical Guide to Their Development and Use New York, Oxford University Press {cited in: Ch 2-16, 520} Sturmer T, Joshi M, Glynn RJ, Avorn J, Rothman KJ, Schneeweiss S (2006) A review of the application of propensity score methods yielded increasing use, advantages in specific settings, but not substantially different estimates compared with conventional multivariable methods J Clin Epidemiol 59(5):437-47 {cited in: Ch 5-27} Sulkowski MS, Thomas DL, Chaisson RE, Moore RD (2000) Hepatotoxicity associated with antiretroviral therapy in adults infected with human immunodeficiency virus and the role of hepatitis C or B virus infection JAMA 283(1):74-80 {cited in: Ch 2-1, 2-98, 2-99, 3-5, 3-9} Sullivan LM, D’Agostino RB Sr (2003) Robustness and power analysis of covariance applied to ordinal scaled data as arising in randomized controlled trials Stat Med 22:1317-1334 {cited in: Ch 2-6} Sun GW, Shock TL, Kay GL (1999) Inappropriate use of bivariable analysis to screen risk factors for use in multivariable analysis Journal of Clinical Epidemiology 49:907-916 {cited in: Ch 5-12, 5-23} Sundar S, Jha TK, Thakur CP, et al (2007) Injectable paromomycin for visceral leishmaniasis in India N Engl J Med 356(25):2571-81 {cited in: Ch 3-11} Sykes MK, Vickers MD, Hull CJ, Winterburn PJ, Shepstone BJ (1991) Principles of Measurement and Monitoring in Anaesthesia and Intensive Care, 3rd ed, Oxford, Blackwell Scientific Publications {cited in: Ch 1-8} Stone GW, Lansky AJ, Pocock SJ, et al (2009) Paclitaxel-eluting stents versus bare-metal stents in acute mycocardial infarction N Engl J Med 360(19):1946-59 {cited in: Ch 215, 4-4 4-5} Tager IB, Weiss ST, Rosner B, Speizer FE (1979) Effect of parental cigarette smoking on pulmonary function in children Am J Epidemiol 110;15-26 {cited in: Ch 2-10} Takkouche B, Regueira-Mendez C, Garcia-Closas R, et al (2002) Intake of wine, beer, and spirits and the risk of clinical common cold Am J Epidemiol 155:853-8 {cited in: Ch 313} Taubes G (1995) Epidemiology faces its limits Science 269(July 14):164-169 {cited in: Ch 36, 3-15} Appendix (revision 15 Aug 2010) p 31 Thara R, Henrietta M, Joseph A, Rajkumar S, Eaton W (1994) Ten year course of schizophrenia—the Madras Longitudinal study Acta Psychiatrica Scandinavica 90:329336 {cited in: Ch 5-20} Thomas DC, Greenland S (1983) The efficiency of matching case-control studies of risk factor interaction J Chronic Dis 38:569-574 {cited in: Ch 5-17} Thompson SG, Barger JA (2000) How should cost data in pragmatic randomised trials be analysed? BMJ 320:1197-2000 {cited in: 5-22} Thompson WD, Kelsey JL, Walter SD (1982) Cost and efficiency in the choice of matched and unmatch case-control studies Am J Epidemiol 116:840-851 {cited in: Ch 5-17} Thompson WW, Price C, Goodson B, et al (2007) Early thimerosal exposure and neuropsychological outcomes at to 10 years N Engl J Med 357;13:1281-1292 {cited in: Ch 5-12} Tonetti MS, D’Aiuto F, Nibali L et al (2007) Treatment of periodontitis and endothelial function N Engl J Med 356(9):911-20 {cited in: Ch 5-18} Tukey J (1977) Exploratory data analysis Reading, MA, Addison-Wesley {cited in: Ch 1-9, 21, 5-11, 5-22} Tukey JW, Ciminera JL, Heyse JF (1985) Testing the statistical certainty of a response to increasing doses of a drug Biometrics 41:295-301 {cited in: Ch 2-8} Twisk JWR (2003) Applied Longitudinal Data Analysis for Epidemiology: A Practical Guide Cambridge, Cambridge University Press {cited in: Ch 3-3, 5-9, 5-15, 5-18, 5-19, 5-20} Ullmann AJ, Lipton JH, Vesole DH, et al (2007) Posaconzole or flucanzole for prophylaxis in severe graph-versus-host disease N Engl J Med 356:335-47 {cited in: Ch 2-15} van Belle G (2002) Statistical Rules of Thumb New York, John Wiley & Sons {cited in: Ch 2-2, 4-1, 5-10, 5-18, 5-15, 5-16, 5-22} van Belle G, Fisher LD, Heagerty PJ, Lumly T (2004) Biostatistics: A Methodology for the Health Sciences, 2nd ed, Hoboken, NJ, John Wiley & Sons {cited in: Ch 3-9, 5-10, 5-11, 5-13} van Buuren S, Boshuizen HC, Knook DL (1999) Multiple imputation of missing blood pressure covariates in survival analysis Statistics in Medicine 18: 681–694 {cited in: Ch 5-9} van den Beld WA, van der Sanden GAC, Janseen AJWM et al (2006) A new motor performance test in a prospective study on children with suspected myopathy Developmental Medicine & Child Neurology 48:739-743 {cited in: Ch 5-14} Appendix (revision 15 Aug 2010) p 32 van der Gaag NA, Rauws EAJ, van Eijck CHJ, et al (2010) Preoperative biliary drainage for cancer of the head of the pancreas N Engl J Med 362:129-37 {cited in: Ch 2-15} van Houwelingen JC, le Cessie S (1990) Predictive value of statistical models Statist Med 8:1303-1325 {cited in: Ch 5-14} Vandenbrouchke JP, von Elm E, Altman DG, et al (2007) Strengthening and reporting of observational studies in epidemiology (STROBE): explanation and elaboration Ann Intern Med 147(8):W-163 to W-194 {cited in: Ch 3-1, 3-8, 5-9} Vanderpump MPJ, Tunbridge WMG, French JM, et al (1995) The incidence of thyroid disorders in the community: a twenty-year follow-up of the Whickham survey Clin Endocrinol 43:55-69 {cited in: Ch 3-1} Vickers AJ, Altman DG (2001) Statistics notes: analysing controlled trials with baseline and follow up measurements BMJ 323:1123-1124 {cited in: Ch 5-16} Vittinghoff E, Glidden DV, Shiboski SC, McCulloch CE (2005) Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models New York, Springer {cited in: Ch 5-11, 5-12, 5-22, 5-23} Vittinghoff E, McCulloch CE (2007) Relaxing the rule of ten events per variable in logistic and Cox regression Am J Epidemiol 165(6):710-718 {cited in: Ch 2-5} Volovics A, van den Brandt PA (1997) Methods for the analysis of case-cohort studies Biom J 39(2):195-214 {cited in: Ch 3-14} Voorrips LE, Goldbohm RA, Brants HA, et al (2000) A prospective cohort study on antioxidant and folate intake and male lung cancer risk Cancer Epidemiol Biomarkers Prev 9:357-65 {cited in: Ch 3-14} Wang TJ, Philimon G, Larson MG (2006) Multiple biomarkers for the prediction of first major cardivascular events and deaths N Engl J Med 355(25):2631-2639 {cited in: Ch 5-14} Ware JH (2006) The limitations of risk factors as prognostic tools N Engl J Med 355(25):26152617 {cited in: Ch 5-14} Webster CS, Merry AF (1997) The standard deviation and the standard error of the mean Anaesthesia 52:183 {cited in: Ch 2-2} Wegman EJ (1990) Hyperdimensional data analysis using parallel coordinates Journal of the American Statistical Association 85: 664-675 {cited in: Ch 5-15} Wei Y, Pere A, Koenker R, He Xuming (2006) Quantile regression methods for reference growth charts Statist Med 25:1369-1382 {cited in: Ch 5-22} Appendix (revision 15 Aug 2010) p 33 Weil M, Bressler J, Parsons P, et al (2005) Blood mercury levels and neurobehavioral function JAMA 293(15):1875-1882 {cited in: Ch 5-2} Weiner DA, Ryan TJ, McCabe CH, Kennedy JW, Schloss M, Tristani F, Chaitman BR, Fisher LD (1979) Exercise stress testing Correlations among history of angina, ST-segment response and prevalence of coronary-artery disease in the Coronary Artery Aurgery Study (CASS) New England Journal of Medicine 301(5):230-5 {cited in: Appendix 1} Weinstein JN, Lurie JD, Tosteson TD, et al (2007) Surgical versus nonsurgical treatment for lumbar degenerative spondylolisthesis N Engl J Med 356(22):2257-70 {cited in: Ch 512} Wellek S (2003) Testing Statistical Hypotheses of Equivalence New York, Chapman & Hall/CRC {cited in: Ch 2-15} Westlake WJ (1981) Bioequivalence testing—a need to rethink (Reader Reaction Response) Biometrics 37:591-593 {cited in: Ch 2-15} Westlake WJ (1988) Bioavailability and bioequivalence of pharmaceutical formulations In, Peace KE (ed), Biopharmaceutical Statistics for Drug Development New York, Marcel Dekker {cited in: Ch 2-15} Whitehead J (1993) Sample size calculations for ordered categorical data Statistics in Medicine 12:2257-2271 {cited in: Ch 2-5, 4-1} Wieand S, Gail MH, James BR, and James KL (1989) A family of nonparametric statistics for comparing diagnostic markers with paired or unpaired data Biometrika 76(3):585-92 {cited in: Appendix dataset descriptions} Wilber K (1985) No Boundary Boston, Shambhala Publications, Inc {cited in: Ch 3-4} Witte JS, Elson RC, Cardon LR (2000) On the relative sample size required for multiple comparisons Statist Med 19;369-372 {cited in: Ch 2-5, 2-8} Wolf FA (1981) Taking the Quantum Leap San Francisco, Harper & Row {cited in: Ch 3-4} Wolfe RA (2000) Statistical analysis, a must for observational studies Kidney International 57; Suppl 74:S-14 S-18 {cited in: Ch 2-10, 5-2} Woodward M (1999) Epidemiology: Study Design and Data Analysis New York, Chapman & Hall/CRC {cited in: Ch 3-6, 5-26} Wright JT, Waterson EJ, Barrison IG, et al (1983) Alcohol consumption, pregnancy and low birthweight Lancet March 26:663-665 {cited in: Ch 5-5, 5-8} Appendix (revision 15 Aug 2010) p 34 Wright SP (1992) Adjusted P-Values for Simultaneous Inference Biometrics 48:1005-1013 {cited in: Ch 2-8} Zhang J, Yu KF (1998) What’s the relative risk? A method of correcting the odds ratio in cohort studies of common outcomes JAMA 280(19):1690-91 {cited in: Ch 3-6} Zhou XH (1993) Maximum likelihood estimators of sensitivity and specificity corrected for verification bias Communication in Statistics—Theory and Methods, 22:3177-98 {cited in: Ch 6-4} Zhou X-H, Obuchowski NA, McClish DK (2002) Statistical Methods in Diagnostic Medicine New York, John Wiley & Sons {cited in: Ch 6-2} Zhou X-H, Stroupe KT, Tierney WM (2001) Regression analysis of health care charges with heteroscedasticity Applied Statistics 50(3):303-312 {cited in: Ch 5-11, 5-22} Zolman JF (1993) Biostatistics: Experimental Design and Statistical Inference New York, Oxford University Press {cited in: Ch 2-8, Ch 3-4} Zou G (2004) A modified Poisson regression approach to prospective studies with binary data Am J Epidemiol 159(7):702-706 {cited in: Ch 3-11} Zung WWK (1965) A self-rating depression scale Arch Gen Psychiatry 12:63-70 {cited in: Ch 2-6} Appendix (revision 15 Aug 2010) p 35 ... construction—still lacking detail >> Section Stata: Data Management, Graphics, and Programming 1-1 Installing Stata and recovering Stata windows installing Stata 3 1-2 adding an icon to the desktop (PC Windows)... run Stata to finish setup updating Stata after setup recoving Windows: load factory settings Getting data into Stata and some other basics 1 opening a Stata formatted data file: 1) clicking on... command directory list (dir) command read in Stata data file (use) command scrolling in Stata? ??s Results window general syntax, or structure, of Stata commands Stata help facility, help command Stata