 |
| |||||
 |
| |||||||||||||||||||||
Biostatistical Methods in Epidemiology
Comment from the Stata technical groupBiostatistical Methods in Epidemiology offers an overview of methodology used for analyzing epidemiologic data and is ideally suited for graduate students in the medical sciences and for practicing medical researchers in general. The book emphasizes nonregression methods, such as life tables and the Mantel–Haenszel estimate of the odds ratio, rather than the sometimes overused and conceptually less accessible regression methods, such as logistic regression and the Cox model. The text is slightly more mathematical than what is usually considered an applied treatment of the topic, yet the mathematics are presented well, and appendices are used to effectively cover the more intensive derivations. The text begins with a brief overview of probability distributions, means and variances, random sampling, and measurement issues, such as confounding and misclassification. Odds ratios are then introduced early on in the context of stratified and unstratified closed-cohort studies. Risk-ratio and risk-difference methods for closed-cohort studies are covered next, followed by a brief introduction to survival analysis, including some terminology; the Kaplan–Meier curve; and Poisson methods for survival data. The text then proceeds with the analysis of case–control data and age-period-cohort analysis. The book closes with some considerations of sample size and power, as well as brief summaries of logistic regression and the Cox model. Table of contents1. Introduction
1.1 Probability
1.2 Parameter Estimation 1.3 Random Sampling 2. Measurement Issues in Epidemiology
2.1 Systematic and Random Error
2.2 Measures of Effect 2.3 Confounding 2.4 Collapsibility Approach to Confounding 2.5 Counterfactual Approach to Confounding 2.6 Methods to Control Confounding 2.7 Bias Due to an Unknown Confounder 2.8 Misclassification 2.9 Scope of this Book 3. Binomial Methods for Single Sample Closed Cohort Data
3.1 Exact Methods
3.2 Asymptotic Methods 4. Odds Ratio Methods for Unstratified Closed Cohort Data
4.1 Asymptotic Unconditional Methods for a Single 2 x 2 Table
4.2 Exact Conditional Methods for a Single 2 x 2 Table 4.3 Asymptotic Conditional Methods for a Single 2 x 2 Table 4.4 Cornfield's Approximation 4.5 Summary of Examples and Recommendations 4.6 Asymptotic Methods for a Single 2 x I Table 5. Odds Ratio Methods for Stratified Closed Cohort Data
5.1 Asymptotic Unconditional Methods for J(2 x 2) Tables
5.2 Asymptotic Conditional Methods for J(2 x 2) Tables 5.3 Mantel–Haenszel Estimate of the Odds Ratio 5.4 Weighted Least Squares Methods for J(2 x 2) Tables 5.5 Interpretation Under Heterogeneity 5.6 Summary of 2 x 2 Examples and Recommendations 5.7 Asymptotic Methods for J(2 x 1) Tables 6. Risk Ratio Methods for Closed Cohort Data
6.1 Asymptotic Unconditional Methods for a Single 2 x 2 Table
6.2 Asymptotic Unconditional Methods for J(2 x 2) Tables 6.3 Mantel–Haenszel Estimate of the Risk Ratio 6.4 Weighted Least Squares Methods for J(2 x 2) Tables 6.5 Summary of Examples and Recommendations 7. Risk Difference Methods for Closed Cohort Data
7.1 Asymptotic Unconditional Methods for a Single 2 x 2 Table
7.2 Asymptotic Unconditional Methods for J(2 x 2) Tables 7.3 Mantel–Haenszel Estimate of the Risk Difference 7.4 Weighted Least Squares Methods for J(2 x 2) Tables 7.5 Summary of Examples and Recommendations 8. Survival Analysis
8.1 Open Cohort Studies and Censoring
8.2 Survival Functions and Hazard Functions 8.3 Hazard Ratio 8.4 Competing Risks 9. Kaplan–Meier and Actuarial Methods for Censored Survival Data
9.1 Kaplan–Meier Survival Curve
9.2 Odds Ratio Methods for Censored Survival Data 9.3 Actuarial Method 10. Poisson Methods for Censored Survival Data
10.1 Poisson Methods for Single Sample Survival Data
10.2 Poisson Methods for Unstratified Survival Data 10.3 Poisson Methods for Stratified Survival Data 11. Odds Ratio Methods for Case–Control Data
11.1 Justification of the Odds Ratio Approach
11.2 Odds Ratio Methods for Matched–Pairs Case–Control Data 11.3 Odds Ratio Methods for (1 : M) Matched Case–Control Data 12. Standardized Rates and Age–Period–Cohort Analysis
12.1 Population Rates
12.2 Directly Standardized Death Rate 12.3 Standardized Mortality Ratio 12.4 Age–Period–Cohort Analysis 13. Life Tables
13.1 Ordinary Life Table
13.2 Multiple Decrement Life Table 13.3 Case-Deleted Life Table 13.4 Analysis of Morbidity Using Life Tales 14. Sample Size and Power
14.1 Sample Size for a Prevalence Study
14.2 Sample Size for a Closed Cohort Study 14.3 Sample Size for an Open Cohort Study 14.4 Sample Size for an Incidence Case–Control Study 14.5 Controlling for Confounding 14.6 Power 15. Logistic Regression and Cox Regression
15.1 Logistic Regression
15.2 Cox Regression A. Odds Ratio Inequality
B. Maximum Likelihood Theory
B.1 Unconditional Maximum Likelihood
B.2 Binomial Distribution B.3 Poisson Distribution B.4 Matrix Inversion C. Hypergeometric and Conditional Poisson Distributions
C.1 Hypergeometric
C.2 Conditional Poisson C.3 Hypergeometric Variance Estimate C.4 Conditional Poisson Variance Estimate D. Quadratic Equation for the Odds Ratio
E. Matrix Identities and Inequalities
E.1 Identities and Inequalities for J(1 x I) and J(2 x I) Tables
E.2 Identities and Inequalities for a Single Table E.3 Hypergeometric Distribution E.4 Conditional Poisson Distribution F. Survival Analysis and Life Tables
F.1 Single Cohort
F.2 Comparison of Cohorts F.3 Life Tables G. Confounding in Open Cohort and Case–Control Studies
G.1 Open Cohort Studies
G.2 Case–Control Studies H. Odds Ratio Estimate in a Matched Case–Control Study
H.1 Asymptotic Unconditional Estimate of Matched-Pairs Odds Ratio
H.2 Asymptotic Conditional Analysis of (1 : M) Matched Case–Control Data References
Index
|
|||||||||||||||||||||
){kind=link}
){kind=link}