Pages that link to "Item:Q4468345"

The following pages link to A Note on the Efficiency of Sandwich Covariance Matrix Estimation (Q4468345):

Displaying 50 items.

• A population‐averaged approach to diagnostic test meta‐analysis (Q4626714) (← links)
• The performances of several modified CIC criteria for working intra-cluster correlation structure selection in GEE analysis (Q4638801) (← links)
• Robust sequential designs for nonlinear regression (Q4707444) (← links)
• Optimal Design Robust to a Misspecified Model (Q4905915) (← links)
• Small sample estimation properties of longitudinal count models (Q4914955) (← links)
• Joint Estimation of the Mean and Error Distribution in Generalized Linear Models (Q4975342) (← links)
• Approaches for the utilization of multiple criteria to select a working correlation structure for use within generalized estimating equations (Q5087936) (← links)
• Robust likelihood inferences for multivariate correlated data (Q5124968) (← links)
• Testing factor–covariate interaction in rank repeated-measures analysis of covariance models (Q5160211) (← links)
• Inference from heteroscedastic functional data (Q5189266) (← links)
• A covariance correction that accounts for correlation estimation to improve finite-sample inference with generalized estimating equations: a study on its applicability with structured correlation matrices (Q5222448) (← links)
• Alternating logistic regressions with improved finite sample properties (Q5283335) (← links)
• Improved standard error estimator for maintaining the validity of inference in cluster randomized trials with a small number of clusters (Q5348687) (← links)
• On small‐sample inference in group randomized trials with binary outcomes and cluster‐level covariates (Q5410275) (← links)
• Criterion for the simultaneous selection of a working correlation structure and either generalized estimating equations or the quadratic inference function approach (Q5420232) (← links)
• Comparison of subject-specific and population averaged models for count data from cluster-unit intervention trials (Q5425038) (← links)
• A Modified Pseudolikelihood Approach for Analysis of Longitudinal Data (Q5434893) (← links)
• A Comparison of Two Bias‐Corrected Covariance Estimators for Generalized Estimating Equations (Q5434932) (← links)
• Toward Best Approximation of Nonlinear Systems: A Case of Models with Memory (Q5485908) (← links)
• A Generalized Estimating Equation Method for Fitting Autocorrelated Ordinal Score Data with an Application in Horticultural Research (Q5757853) (← links)
• Standard Errors for Nonparametric Regression (Q5861018) (← links)
• A comparison study on modeling of clustered and overdispersed count data for multiple comparisons (Q5861164) (← links)
• Sample size and power analysis for stepped wedge cluster randomised trials with binary outcomes (Q5880076) (← links)
• Power analysis for cluster randomized trials with multiple binary co‐primary endpoints (Q6047743) (← links)
• Smooth tests of goodness of fit for the distributional assumption of regression models (Q6051661) (← links)
• Marginal Proportional Hazards Models for Clustered Interval-Censored Data with Time-Dependent Covariates (Q6055739) (← links)
• Practical Review and Comparison of Modified Covariance Estimators for Linear Mixed Models in Small‐sample Longitudinal Studies with Missing Data (Q6067147) (← links)
• Power considerations for generalized estimating equations analyses of four‐level cluster randomized trials (Q6068806) (← links)
• Variance estimation in inverse probability weighted Cox models (Q6076525) (← links)
• Small‐sample inference for cluster‐based outcome‐dependent sampling schemes in resource‐limited settings: Investigating low birthweight in Rwanda (Q6079493) (← links)
• Multivariate survival analysis in big data: A divide‐and‐combine approach (Q6079569) (← links)
• Sample size and power considerations for cluster randomized trials with count outcomes subject to right truncation (Q6091683) (← links)
• Improving sandwich variance estimation for marginal Cox analysis of cluster randomized trials (Q6141309) (← links)
• Effect of measurement error size in linear heteroscedastic measurement error models (Q6141712) (← links)
• Approximate likelihood and pseudo‐likelihood inference in meta‐analysis of diagnostic accuracy studies accounting for disease prevalence and study design (Q6189820) (← links)
• Clustered restricted mean survival time regression (Q6594186) (← links)
• The effect of number of clusters and magnitude of within-cluster homogeneity in outcomes on the performance of four variance estimators for a marginal multivariable Cox regression model fit to clustered data in the context of observational research (Q6618321) (← links)
• Leveraging baseline covariates to analyze small cluster-randomized trials with a rare binary outcome (Q6625360) (← links)
• Power and sample size requirements for GEE analyses of cluster randomized crossover trials (Q6625668) (← links)
• A comparison of bias-adjusted generalized estimating equations for sparse binary data in small-sample longitudinal studies (Q6625805) (← links)
• Bias-reduced and separation-proof GEE with small or sparse longitudinal binary data (Q6627143) (← links)
• Design and analysis considerations for cohort stepped wedge cluster randomized trials with a decay correlation structure (Q6627314) (← links)
• A note on the bias of standard errors when orthogonality of mean and variance parameters is not satisfied in the mixed model for repeated measures analysis (Q6627323) (← links)
• Sample size estimation for stratified individual and cluster randomized trials with binary outcomes (Q6627350) (← links)
• Uncertainty in the design stage of two-stage Bayesian propensity score analysis (Q6627422) (← links)
• Maintaining the validity of inference in small-sample stepped wedge cluster randomized trials with binary outcomes when using generalized estimating equations (Q6627545) (← links)
• Sample size calculation in three-level cluster randomized trials using generalized estimating equation models (Q6627623) (← links)
• Fitting marginal models in small samples: a simulation study of marginalized multilevel models and generalized estimating equations (Q6628027) (← links)
• Sample size considerations for matched-pair cluster randomization design with incomplete observations of binary outcomes (Q6628035) (← links)
• Power calculation for analyses of cross-sectional stepped-wedge cluster randomized trials with binary outcomes via generalized estimating equations (Q6628208) (← links)