Interpreting regression models using StataPage 9Page
AuthorVince Wiggins, StataCorp Question: We are usingquadchkafter fitting a random-effects logistic regression model usingxtlogit. Using the default (12) quadrature points and runningquadchkon 8 and 16 points, we are getting a relative difference for thelnsig2uparameter of 0.34. The manual indica...
11 LOGISTIC REGRESSION - INTERPRETING PARAMETERS 11 Logistic Regression - Interpreting Parameters Let us expand on the material in the last section, trying to make sure we understand the logistic regression model and can interpret Stata output. Consider first the case of a single binary predictor,...
Clarify is a program that uses Monte Carlo simulation to convert the raw output of statistical procedures into results that are of direct interest to researchers, without changing statistical assumptions or requiring new statistical models. The program, designed for use with the Stata statistics ...
Using a dataset based on the General Social Survey, Mitchell starts with a basic linear regression with a single independent variable and then illustrates how to tabulate and graph predicted values. Mitchell focuses on Stata'smarginsandmarginsplotcommands, which play a central role in the book and...
Using a dataset based on the General Social Survey, Mitchell starts with a basic linear regression with a single independent variable and then illustrates how to tabulate and graph predicted values. Mitchell focuses on Stata'smarginsandmarginsplotcommands, which play a central role in the book and...
Clarify is a program that uses Monte Carlo simulation to convert the raw output of statistical procedures into results that are of direct interest to researchers, without changing statistical assumptions or requiring new statistical models. The program, designed for use with the Stata statistics package...
Interpreting Linear Regression Coefficients: A Walk Through Output Learn the approach for understanding coefficients in that regression as we walk through output of a model that includes numerical and categorical predictors and an interaction.
It is a simple logistic regression as you use to estimate in Stata or SPSS. Should I use StdYX for continous and StdY for the binary covariates even when the two types of covariates are in one and the same model? I have a strange feeling by using for some covariates the coefficients ...
Interpreting and Visualizing Regression Models Using Stata, by Michael N. Mitchell (Stata Press, College Station, Texas, 2012), pp. xxix + 558Regression analysisNo abstract is available for this article.doi:10.1111/1475-4932.12023FosterGigi