You can check for homoscedasticity in Stata by plotting the studentized residuals against the unstandardized predicted values. Assumption #6: Your data must not show multicollinearity, which occurs when you have
At its core, multicollinearity implies that the independent variables in your regression model are not truly independent. They share a significant amount of variance, making it difficult for the model to isolate the individual effect of each predictor on the dependent variable. Imagine trying to unta...
Assumption #4: Your data must not show multicollinearity, which occurs when you have two or more independent variables that are highly correlated with each other. Assumption #5: There needs to be a linear relationship between any continuous independent variables and the logit transformation of the ...
break down for multiple reasons (e.g., poor initial conditions or multicollinearity in a bootstrap sample). When it does, stata stops. Is there a way of convincing stata to make a note and keep going? In other words, can ML report an error in a manner which can be identified without ...
To delete a command in Stata, you should first open the Stata command window and type the “ edit ” command to open the Do-file Editor. From there, you can search and select the command you want to delete, then hit “ Ctrl + X ” or right-click the selection and select “Cut” ...
endogeneity-corrected estimations for the full model from Eq.4. We use Model 2 to examine the main-effect hypothesis and Model 4 to test the moderation hypotheses. For each model, we also report (Table4) the highest variance inflation factor (VIF) to verify that multicollinearity is not an ...
For a robustness check, we compared the PMLE results with the multi-level mixed-effect logit and probit model. It can also be used to fit different model outcomes. The panel data were estimated using the firthlogit, melogit and meprobit commands in Stata 17. To deal with endogeneity, we ...
To implement these analyses, we need a flexible estimator for multi-equation econometric models that can accommodate non-linearity if need be (i.e., if researchers choose to use a control function approach). MLE is suitable for this purpose and can be implemented in thecmpmodule for Stata, ...
Learn about factor analysis - a simple way to condense the data in many variables into a just a few variables.
In this paper, all calculations and regression analyses are performed using the statistical software Stata 14.0. First, the linear correlation between factors is tested to ensure that the standard error of the regression results will not increase due to multicollinearity. In this paper, the variance...