Traditional SEM overly focuses on LISREL equations to the detriment of dealing with measurement error
Problems with using odds ratios as effect sizes in binary logistic regression and alternative approaches
How do you communicate the evidence for the practical significance of an intervention using Bayesian methods?
When data are not so informative, it pays to choose the sum score over the factor score
Multidimensional CFA with RStan
Possibility of heteroskedasticity is a good reason not to dichotomize a continuous variable for use as outcome in logistic regression.
Should you perform logistic regression on a dichotomized continuous variable when you have access to the continuous variable? I'm not sure.
Two group mean and variance comparisons
Modeling the error variance to account for heteroskedasticity
Simulating data from regression models
Using binary regression software to model ordinal data as a multivariate GLM
Using glmer() to perform Rasch analysis
A Chi-Square test of close fit in covariance-based SEM
Misspecification and fit indices in covariance-based SEM
Little's MCAR test at different sample sizes
Theil-Sen regression in R
Linear regression with violation of heteroskedasticity with small samples
On the interpretation of regression coefficients