General guidelines for choosing a statistical analysis based on the number of dependent variables, the nature of your independent variables, and whether the dependent variable is an interval variable, ordinal or categorical variable, and whether it is normally distributed. From UCLA's Institute for Digital Research and Education.
his site provides online seminars designed to improve skills in statistical computing packages and statistical techniques. Topics covered include: Stata, R, SAS, SPSS, Mplus and Latent Variable Analysis, and more.
In this article, we’ll describe the Cox regression model and provide practical examples using R software. The Cox proportional-hazards model is essentially a regression model commonly used statistical in medical research for investigating the association between the survival time of patients and one or more predictor variables.
DAGitty is a browser-based environment for creating, editing, and analyzing causal models (also known as directed acyclic graphs or causal Bayesian networks).
Tidy, analyze, and plot causal directed acyclic graphs (DAGs). ggdag uses the powerful dagitty package to create and analyze structural causal models and plot them using ggplot2 and ggraph in a consistent and easy manner.
Interpreting the logistic regression’s coefficients is somehow tricky. Looking at some examples beside doing the math helps getting the concept of odds, odds ratios and consequently getting more familiar with the meaning of the regression coefficients. The following examples are mainly taken from IDRE UCLE FAQ Page and they are recreated with R.
GIF offers workshops, office hours, online trainings, geospatial data, networking and funding opportunities, and more. They also facilitate free UCB access to ArcGIS.
The Department of Statistics operates a free consulting service for members of the campus community. Advanced graduate students, under faculty supervision, consult by appointment in the fall and spring semesters. We do not run the consulting service during the summer.
