Sample size evaluation for a multiply matched case-control study using the score test from a conditional logistic (discrete Cox PH) regression model

Sample size determination for logistic regression

The problem of sample size estimation is important in medical applications, especially in cases of expensive measurements of immune biomarkers. This paper describes the problem of logistic regression analysis with the sample size determination algorithms, namely the methods of univariate statistics, logistics regression, cross-validation and Bayesian inference. The authors, treating the regr...

A score test for determining sample size in matched case-control studies with categorical exposure.

The paper considers the problem of determining the number of matched sets in 1 : M matched case-control studies with a categorical exposure having k + 1 categories, k > or = 1. The basic interest lies in constructing a test statistic to test whether the exposure is associated with the disease. Estimates of the k odds ratios for 1 : M matched case-control studies with dichotomous exposure and fo...

Unconditional or Conditional Logistic Regression Model for Age-Matched Case–Control Data?

Matching on demographic variables is commonly used in case-control studies to adjust for confounding at the design stage. There is a presumption that matched data need to be analyzed by matched methods. Conditional logistic regression has become a standard for matched case-control data to tackle the sparse data problem. The sparse data problem, however, may not be a concern for loose-matching d...

Simulation for estimating statistical power of conditional logistic regression analysis in matched case-control study

Sample Size Determination for Logistic Regression: A Simulation Study

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