Stat Computing > Stata > Code

Stata Code Fragments

These pages contain Stata commands and Stata programs with a minimum of documentation or explanation.  These pages often reflect samples that we have created in solving a problem for someone during consulting.  If we do not have time to make a proper FAQ or Learning Module, we place the example program here so it may be publicly available until we have time to make a proper FAQ page or Learning Module page.  Until then, we hope that these example may prove useful to some of you. If you are not sure if you are properly using any of these code fragments (and you are a member of the UCLA research community) please use our consulting services so we may help you properly use these examples.  Many of these examples are tricky and complicated, so if you are in doubt, please let us assist you.

• Comparing regression coefficients across groups using suest
• Combining histogram and boxplot in one graph
• Computing spells
• Using sureg
• Testing bootstrapping
• Testing use of hotdeck
• Getting interactions of dummy variables
• Permutation tests in Stata
• Graphing residuals in logistic regression in Stata
• Working across variables
• Using xtreg  
• Descriptives, ttests, anova and regression
• ANOVA
• Using "for"
• Using and saving graphs in Stata in batch mode
• Getting adjusted values in probit
• Understanding odds ratios in binary logistic regression
• Understanding RR ratios in multinomial logistic regression
• Graphing binary logistic regression given parameters
• Graphing ordinal logistic regression given parameters
• Matching kids and parents in ipums data
• Graphing interactions of two continuous variables using postgr
• Comparing OLS and logistic for analyzing binary outcomes
• Many boxplots (Stata 8)
• Merging the NSAF data files
• Computing intraclass correlations in Stata
• Spaghetti plots
• Simulating Discrete (Geometric, Poisson and Zero-Inflated Poisson, Negative Binomial and Zero-Inflated
  Negative Binomial) Random Variables
• Choosing between nonnested models
• Replacing All Character Values in a String Variable with a Single Numeric or Character Value
• Displaying hazard ratio by different baseline characteristics
• Reading Stata data into Mata
• Graphing predicted probabilities with two interaction terms
• Creating a pyramid plot by subgroup
• Using ml commands to maximize a user specified likelihood function
• Creating an adjacency matrix

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