To: statalist@hsphsun2.harvard.edu Subject: Re: st: Re: How to delete studentized residuals with absolutevalues greater than or equal to two after conducting areg procedure? Dear George, Assessing "the robustness of the analysis results" usually involves much more than rerunning the model afte...
Assumption #3: You should have independence of observations (i.e., independence of residuals), which you can check in Stata using the Durbin-Watson statistic. Assumption #4: There needs to be a linear relationship between (a) the dependent variable and each of your independent variables, and...
Plot() does only show Residuals vs. Fitted, but not other diagnostic plots; par(mfrow=c(2,2)) already applied How to Read Large JSON file in R? Figure Caption in R markdown Ggplot troubleshoot: Error: Aesthetics must be either length 1 or the same as the data (24): x, y...
How would I derive a linear regression equation 'under the logarithm' with respect to output per worker in an augmented standard Solow model? What does a p-value not tell you? Choose the correct answer. Which type of categorical variables are used to incorporate major events in time...
To get it, create a new variable in which you subtract the mean from the original value, then divide that by the standard deviation. 3. Use those standardized versions in the regression. Could this take a while? Yup. But if that’s what the journal requires you report, just do it. A...
1) run OLS regression where chine_exp is the dep var and distance is the indep var along with the rest of the variables included in your original equation. 2) get the residuals from the regression "vhat". 3) run your equation including the residuals from the first OLS as follow ...
(e.g., studentized residuals) and leverage (Cook’s distance) can help detect the presence of outliers and evaluate their influence (Viechtbauer and Cheung2010). Moreover, several statistical procedures can be used to test for publication bias (Harrison et al.2017; Kepes et al.2012), ...
Missing data in covariates can result in biased estimates and loss of power to detect associations. It can also lead to other challenges in time-to-event analyses including the handling of time-varying effects of covariates, selection of covariates and t
For illustrative purposes, we set the covariance of the residuals in the outcome and treatment selection equations at. This strikes us intuitively as a substantial level of endogeneity for the purposes of the simulations. Next, we set the correlation of the instrument with treatment selection to ...
If you can explain how autoreg calculates serial correlation of residuals for your model, then somebody well qualified may be able to comment. You could try betting that someone on this list knows what autoreg in SAS does, but you're less likely to get a good answer. You can't easily ...