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Outline

Title
Abstract
Introduction
Generating Data Files
Importing a Data File from Other Programs
Copy a Variable Into the Same Data File
Browsing Stata Outputs in Results Window
Knowing the Dataset
Generating Brief Description of a Dataset
Sorting of Data
Data Cleaning and Data Screening
Data Management
Recoding of Data
Combining Data Into a New Variable
Data Transformation
Relocating Variables in the Dataset
Selecting a Sub-Group for Analysis
Transformation of Data Formats
Data Analysis: Descriptive Statistics
Assessing Normality of Data
Checking Data for Normality
Testing of Hypothesis
Alternative Hypothesis (H a )
Analysis of Variance (Anova)
Interpretation of Post Hoc Test Results
Stratified Analysis
Hypothesis Test of Proportions
Commands for Multiple Linear Regression Analysis
Backward Selection Method
Forward Selection Method
Survival Analysis
Preparing Data for Analysis
Commands for Kaplan-Meyer Method
Hypothesis
References

Data Analysis using STATA

Profile image of Dr. Russell KabirDr. Russell KabirProfile image of MT IslamMT Islam

2022, ASA Publications

https://doi.org/10.13140/RG.2.2.18525.74725
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270 pages

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1 file

Abstract

Anyone can download it from the links, print it out for personal use, and share it with others, but it is strictly prohibited to use it for any kind of profit-making venture without the written permission of the first author. Its contents may be used and incorporated into other materials with proper acknowledgements and citations. The datasets provided in the links and used in this book are hypothetical and can be used for practice.

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Acknowledgments In addition to the people at Stata –particularly, Bill Gould, Vince Wiggins
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2010

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Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may no be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. For general information on our other products and services or for technical support, please contact our Customer Care Department within the United States at (800) 762-2974, outside the United States at (317) 572-3993 or fax (317) 572-4002. Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic formats. For more information about Wiley products, visit our web site at www.wiley.com.

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References (132)

  1. Acock AC. (2014). A Gentle Introduction to Stata. (4 th Edition). Stata Press, StataCorp LP, Texas
  2. Advanced Research Computing: Statistical Methods and Data Analytics. Regression with Stata chapter 2 -regression diagnostics: UCLA. https://stats.oarc.ucla.edu/stata/webbooks/reg/chapter2/stata-webbooksregres sionwith-statachapter-2-regression-diagnostics/
  3. Altman DG. (1992). Practical Statistics for Medical Research (1 st Edition). Chapman & Hill.
  4. Anderson M, Nelson A. Data analysis: Simple statistical tests. FOCUS on Field Epidemiology: UNC School of Public Health. North Carolina Centre for Public Health Preparedness; Vol 3(6).
  5. Barros AJD, Hirakata VN. Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the preva- lence ratio. BMC Medical Research Methodology 2003; 3(21):1-13. http://w- ww.biomedcentral.com/1471-2288/3/21
  6. Bergmire-Sweat D, Nelson A, FOCUS Workgroup. Advanced Data Analysis: Methods to Control for Confounding (Matching and Logistic Regression). Focus on Field Epidemiology: UNC School of Public Health. North Carolina Centre for Public Health Preparedness; Volume 4, Issue 1.
  7. Chan YH. Biostatistics 103: Qualitative Data -Tests of Independence. Singapore Med J 2003; Vol 44(10):498-503.
  8. Chan YH. Biostatistics 104: Correlational Analysis. Singapore Med J 2003; Vol 44(12):614-619.
  9. Chan YH. Biostatistics 201: Linear Regression Analysis. Singapore Med J 2004; Vol 45(2):55-61.
  10. Chan YH. Biostatistics 202: Logistic regression analysis. Singapore Med J 2004; Vol 45(4):149-153.
  11. Chan YH. Biostatistics 203. Survival analysis. Singapore Med J 2004; Vol 45(6):249-256.
  12. Chan YH. Biostatistics 3.5. Multinominal logistic regression. Singapore Med J 2005; 46(6):259-268.
  13. Daniel WW. (1999). Biostatistics: A Foundation for Analysis in the Health Science (7 th Edition). John Wiley & Sons, Inc.
  14. Daniels L, Minot N. An introduction to statistics and data analysis using Stata. (2020). SAGE Publications, Inc: USA.
  15. Eric Vittinghoff E, Glidden DV, Shiboski SC, McCulloch CE. Regression methods in biostatistics: Linear, Logistic, Survival, and Repeated Measures Models. (2012). 2 nd ed. Springer New York.
  16. Gordis L. (2014). Epidemiology (5 th Edition). ELSEVIER Sounders.
  17. Hamilton LC. (2013). Statistics with Stata (8 th Edition). Brooks/Cole Cengage Leaning: USA.
  18. Hess KR. Graphical methods for assessing violations of the proportional hazards assumption in Cox regression. Stat Med 1995;14(15):1707-23. doi: 10.1002/sim.4780141510.
  19. Islam MT, Kabir R, Nisha M. (2021). Learning SPSS without Pain (2 nd Edition. ASA publications, Dhaka.
  20. Juul S, Frydenberg M. (2014). An introduction to Stata for health researchers (5 th Edition). Stata press, StataCorp, Texas.
  21. Katz MH. (2009). Study Design and Statistical Analysis: A Practical Guide for Clinicians. Cambridge University Press.
  22. Katz MH. (2010).Evaluating Clinical and Public Health Interventions -A Practical Guide to Study Design and Statistics. Cambridge University Press.
  23. Katz MH. (2011). Multivariable Analysis: A Practical Guide for Clinicians and Public Health Researchers (3 rd Edition). London, Cambridge University Press.
  24. Katz MH. Multivariable Analysis: A Primer for Readers of Medical Research. Ann Intern Med 2003; 138:644-650.
  25. Khamis H. Measures of Association: How to Choose? JDMS 2008; 24:155-162.
  26. Lee J, Chia KS. Estimation of prevalence rate ratios for cross sectional data: an example in occupational epidemiology. British Journal of Industrial Medicine 1993; 50:861-864.
  27. Long JS, Freese J. Regression models for categorical dependent variables using Stata. Stata publication. StataCorp LP, Texas.
  28. Malek MH, Berger DE, Coburn JW. On the inappropriateness of stepwise regression analysis for model building and testing. Eur J Appl Physiol 2007; 101: 263-264. https://doi.org/10.1007/s00421-007-0485-9.
  29. Pfaff T. A brief introduction to Stata with 50+ basic commands. (2009). Institute for Economic Education, University of Münster.
  30. Rabe-Hesketh S, Everitt B. A Handbook of Statistical Analyses using Stata. (2004). 3 rd ed. Chapman & Hall/CRC.
  31. Reboldi G, Angeli F, Verdecchia P. Multivariable Analysis in Cerebrovascular Research: Practical Notes for the Clinician. Cerebrovasc Dis 2013; 35:187-193. DOI: 10.1159/000345491.
  32. Schlesselman JJ, Stolley PD. (1982). Case-Control Studies: Design, Conduct, Analysis. Oxford University Press, Oxford, New York.
  33. Stata press. (2009). Stata multivariate statistics reference manual release 11. Stata Publication. StataCorp LP, Texas.
  34. Stata press. (2012). Data Analysis Using Stata (3 rd Edition). StataCorp LP, Texas.
  35. Szklo M, Nieto FJ. (2007). Epidemiology: Beyond the Basics (2 nd Edition). Jones and Bartlett Publishers.
  36. Tabachnik BG, Fidell LS. (2007). Using multivariate statistics (5 th Edition). Boston: Pearson Education.
  37. Thompson ML, Myers JE, Kriebel D. Prevalence odds ratio or prevalence ratio in the analysis of cross sectional data: what is to be done? Occup Environ Med 1998; 55:272-277.
  38. UCLA. Advanced Research Computing: Statistical Methods and Data Analytics; Repeated Measures Analysis with Stata. https://stats.oarc.ucla.edu/stata/semi- nars/repeated-measures-analysis-with-stata/
  39. Whittingham M, Stephens P, Bradbury R, Freckleton R. Why do we still use stepwise modelling in ecology and behavior? Journal of Animal Ecology 2006; 75(5):1182-1189.
  40. Williams R. Using the margins command to estimate and interpret adjusted predictions and marginal effects. The Stata Journal 2012;12(2):308-331.
  41. Zwiener I, Blettner M, Hommel G: Survival analysis-part 15 of a series on evaluation of scientific publications. Dtsch Arztebl Int 2011; 108(10):163-9. DOI: 10.3238/arztebl.201 1.0163
  42. Subject index with chapters and sections Adjusted odds ratio, 13.3, 13.3.1, 17.2.1.1, 17.2.6.1
  43. Adjusted R-squared, 6.2.4.1, 16.1.2, 16.2.3 Analysis of covariance (ANCOVA), 9, 21 Analysis of variance (ANOVA), 9, 11.1, 11.2 Average interitem correlation, 22.1, 22.1.1
  44. Backward LR, 17.2.3
  45. Backward, 16.2.5.1, 17.2.3, 19.2 Bar graph, 7.4, 7.4.1, 7.4.2
  46. Bartlett's test, 11.1.2, 11.1.5
  47. Beta, 16.2.2, 16.2.3 Binary logistic regression, 17, 17.2
  48. Bland Altman test, 9
  49. Bonferroni's test, 11.1.3, 11.1.5, 11.2.3, 12.1.2, 21.1.1, 21.1.2, 21.2.1
  50. Box and Plot, 4.2, 7.3, 11.1.3
  51. Breslow's test, 19.1.3
  52. Censored time, 19 Central tendency, 6.2
  53. Chi-square test of independence, 9, 13.1 Class interval, 5.3 Classification table, 17.2.2.2
  54. Codebook, 3.3.2 Combine data, 5.4 Conditional logistic regression, 17, 17.2.6 Confidence interval, 6.2
  55. Confounding factor, 13.3, 16.2.5, 17.2, 17.2.4 Converting variables, 5.1 Correlation, 15.1 Correlation coefficient, 15.1, 15.1.2, 16.2.4.1
  56. Correlation matrix, 15.1.2, 16.2.4.1, 17.2.2.1, 22.1
  57. Cronbach's alpha, 22.1
  58. Cross-tabulation, 6.1, 13.1 Cumulative probability of survival, 19, 19.1.2, 19.1.3, 19.2, 19.2.1
  59. Data cleaning 4 Data file generation, 2.1 Data file import, 2.1.3
  60. Data file, 3.1, 3.1.1
  61. Data screening, 4
  62. Data transformation, 3.1.2.5, 5.5
  63. Dispersion, 6.2
  64. Durbin-Watson test, 16.2.4.6
  65. Egen, 5.10 Event time, 19
  66. Exponential, 17.1, 17.2.1.1 Extraction of duration, 5.7
  67. Fisher's exact test, 9, 13.1.1, 13.1.2
  68. Forward LR, 17.2.3
  69. Frequency, 6.1
  70. Friedman test, 9, 20.5
  71. Graph, 7
  72. Greenhouse-Geisser test, 12.1.2
  73. Hazard ratio, 19.2, 19.2.1
  74. Help, 3.6
  75. Histogram, 7.1, 8.1, 8.1.1 Homogeneity of regression slopes, 21.1, 21.1.2 Homogeneity of variances, 11, 11.1.2, 11.2, 21.1
  76. Homoscedasticity, 16.1, 16.2.4, 16.2.4.4
  77. Hosmer-Lemeshow test, 17.2.2.2
  78. Huynh-Feldt test, 12.1.2 Hypothesis testing, 9 Independent samples t-test, 9, 10.2, 10.2.2, 10.2.3
  79. Interaction, 11.2, 11.2.2, 13.3, 13.3.1, 16.2.2, 17.2.4, 21.1, 21.1.2, 21.2, 21.2.2 Iteration, 19.2.1, 19.2.2 Interitem correlation, 22.1, 22.1.1
  80. Kaplan-Meier method, 19, 19.1, 19.1.2
  81. Kendall's tau-b, 15.2
  82. Kolmogorov-Smirnov test Kruskal-Wallis test, 9, 20.4
  83. Kurtosis, 6.2, 6.2.1
  84. Levene's test, 10.2.1 Likelihood ratio, 17.2.1.1 Line graph, 7.5 Linear regression, 16
  85. Linearity, 16.2.4.2 Log file, 3.1.2 Log rank test, 19.1.2, 19.1.3 Logistic regression diagnostics, 17.2.2 Logistic regression model, 17.1 Logistic regression, 17 Logit transformation, 17.1 Log-minus-log plot, 19.2.4 Long format, 5.12, 20.5
  86. Mann-Whitney U test, 9, 20.1 Marginal value, 18.2, 21.2.1 Margins plot, 18.2
  87. Mauchly's test, 12.1.2 McNemer test, 9 Median survival time, 19, 19.1.2, 19.1.3, 19.2 Median test, 20.2
  88. Multicollinearity, 16.2.4, 16.2.4.1, 16.2.4.4, 17.1, 17.2.2.1, 19.2.4
  89. Multinominal logistic regression, 9, 17, 18 Multiple comparisons, 11.1.3, 11.1.4, 11.2.3, 21.1.2
  90. Multiple linear regression, 9, 16.2, 16.2.2, 16.2.3
  91. Negative predictive value, 17.2.2.2
  92. Numeric variable, 5.1.1, 5.1.2 Odds ratio (OR), 13.2
  93. One-sample test of proportion, 14.1
  94. One-sample t-test, 9, 10.1
  95. One-way ANCOVA 21.1
  96. One-way ANOVA 11.1
  97. One-way repeated measures ANOVA, 12.1 Outliers, 4.2, 6.2.1, 7.2, 7.3, 8.1.1, 16.2.4.5
  98. Paired t-test, 9, 10.3, 10.3.1, 10.3.2 Partial correlation, 15.3
  99. Pearson's chi-square, 13.1.2
  100. Percentile, 6.2, 6.2.1
  101. Poisson regression, 9, 17.3, 17.3.1 Positive predictive value, 17.2.2.2 Post hoc test, 11.1.3, 11.1.4, 11.2.3, 11.1.5 Post-estimation commands, 17.2.2.4, 18.2, Prevalence odds ratio, 17.3 Prevalence ratio, 17.3 Proportion test, 14 Proportional hazards analysis, 9, 17.3, 19.2 Proportional odds regression, 9, 17
  102. Proportionality assumption, 19.2.4
  103. Pseudo R-squared, 17.2.1.1, 17.2.6.1, 18.1 Q-Q plot, 8.1, 8.1.1
  104. Quartile, 6.2.1
  105. Quintile, 22.2
  106. Recoding, 5.2 Regression coefficient, 16.2, 16.2.3, 16.2.4.1, 16.2.5.3, 17.2.1.1, 17.2.2.1, 17.2.6
  107. Regression diagnostics, 16.2.4, 17.2.2 Regression equation, 16.1, 16.1.2, Ordinal logistic regression, 17 16.2.3 Relative risk (RR), 13.2 Reliability of scales, 22.1 Relocation of variables, 5.8 ROC curve, 17.2.2.
  108. R-squared, 16.1.2, 16.2.3, 16.2.4.3, 16.2.5.3
  109. Scatterplot, 7.2
  110. Scheffe's test, 11.1.3, 21.1.2 Score calculation, 5.6
  111. Sdtest, 10.2.1
  112. Search, 3.6
  113. Sensitivity, 17.2.2.2
  114. Shapiro Wilk test, 8.1, 8.1.1 Simple linear regression, 16.1
  115. Skewness, 6.2, 6.2.1
  116. Skewness-kurtosis (S-K) test, 8.1, 8.1.1
  117. Sorting, 3.4, 6.3, 16.2.4.5
  118. Specificity, 17.2.2.2 Sphericity assumption, 12.1
  119. Stata files, 3
  120. Stata windows, 1.2
  121. Stepwise, 16.2.5, 16.2.5.1, 16.2.5.2, 16.2.5.3, 17.2.3, 19.2.1
  122. Sub-group, 5.9 Survival analysis, 19, 19.1 Survival curve, 19.1.2, 19.1.3, 19.2.1
  123. Symbols, 3.5
  124. Syntax, 3.2
  125. Tarone-Ware test, 19.1.2, 19.1.3 Test for independence, 16.2.4.6
  126. Time extraction, 5.7
  127. Tolerance, 16.2.4.1 Total score calculation, 5.6 Transformation of data, 5.5 t-test, 9, 10, 10.1, 10.2, 10.3
  128. Tukey's test, 11.1.3, 11.1.5, 21.1.2
  129. Two-way ANOVA 11.2
  130. Two-way repeated measures ANOVA Unconditional logistic regression, 17, 17.2.1 Testing of hypothesis, 9 Unequal variances, 11.1.5 Variable insertion, 2.1.4.2 Variance inflation factor (VIF), 16.2.4.1 Version, 1.1
  131. Wilcoxon Signed Ranks test, 9, 20.3
  132. Wilk's lambda, 12.1.2

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