Why is my command not working with factor-variable syntax and/or collinear variables in Stata 11? Answer: As of Stata 11, variables are no longer dropped because of collinearity. Instead, these variables are omitted and are labeled with an “o.” operator in the column names of the resultin...
The collapse command in Stata is used to create summary variables from an existing dataset. It allows you to aggregate observations within groups, summarizing them into a new dataset. Collapsing a dataset can be useful for creating summary statistics, such as the mean and standard deviation, for ...
This yields margins that are numerically equivalent to the predicted marginal means we calculated by omitting atmeans. Similarly, when it comes to interactions between two categorical variables, Stata knows how to determine the appropriate proportion for each level of the interaction when asbalanced is...
Before moving to the R and RStudio installation, we need to make sure of some basic things for the smooth run. You need to have your Linux system ready with a user with sudo rights along with access to the internet for getting the required packages. Step 1: Installing R Package in Linu...
To facilitate comparisons to prior findings, we use the same control variables as Dalton (2008), but a different dependent variable. In contrast to Dalton’s approach of using separate political acts as dependent variables in a series of separate ordinary least squares (OLS) regression analyses, ...
Learn about factor analysis - a simple way to condense the data in many variables into a just a few variables.
It is included in the core module and asked annually each year: “During the past 12 months, have you had either a flu shot or a flu vaccine that was sprayed in your nose?”, where 1 = yes and 0 = no. My independent variables of interest are race/ethnicity identity and ...
MCAR occurs when the probability of missing data on a variable is unrelated to the values of that variable or any other variables in the datasets. In other words, the columns with missing data do not have an interdependency. The missing data is completely random and does not introduce bias....
Socially sustainable practices of MNBs positively impact access to 1) a bank account, 2) credit, and 3) savings among the lowest-income groups in developing countries. • When MNBs combine socially sustainable practices with their business model, they build trust and reduce risks in the develo...
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