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Results tagged with regression
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user 307
Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.
7
votes
Accepted
A better presentation of linear regression model
One section of the paper is devoted to "Plotting Regression Coefficients". …
- 7,330
8
votes
Mediation model with linear regression
You can run regression models separately, if you follow the Baron-Kenny approach. …
- 7,330
16
votes
Accepted
How can I use logistic regression betas + raw data to get probabilities
I am simulating data for a simple bivariate logistic regression model $log(\frac{p}{1-p})=\beta_0 + \beta_1 \cdot x$:
> set.seed(3124)
>
> ## Formula for converting logit to probabilities
> ## Source …
- 7,330
7
votes
How to do meta-regression analysis with SPSS?
He offers spss, stata, and sas macros for performing meta-analytic analyses (including meta-regression; metareg.sps) + PPT slides (analysis.ppt, interpretation.ppt). …
- 7,330
4
votes
Is it necessary to report the bivariate correlations when reporting logistic regression?
You might want to check the following papers which discuss how to report findings from logistic regression analysis:
Reporting results of a logistic regression
Recommendations for the Assessment and … Reporting of Multivariable Logistic Regression in Transplantation Literature
Logistic regression in the medical literature: Standards for use and reporting, with particular attention to one medical domain …
- 7,330
68
votes
How exactly does one “control for other variables”?
In the following I am referring to this PDF document: "Multiple Regression Analysis: Estimation", which has a section on "A 'Partialling Out' Interpretation of Multiple Regression" (p. 83f.). … weight for lmEC.resid (see column Estimate, $\beta_{lmEC.resid}=0.50$) in this simple regression is equal to the multiple regression weight for covariate, which also is $0.50$ (see @EpiGrad's answer …
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9
votes
Interpretation of variance in multilevel logistic regression
Consequently, the values of the regression coefficients and higher-level variances are also rescaled, in addition to
any real changes resulting from the changes in the model. … These
implicit scale changes make it impossible to compare regression
coefficients across models, or to investigate how variance components
change. …
- 7,330