By declaring data type, you enable Stata to apply data munging and analysis functions specific to certain data types TIME SERIES OPERATORS L. lag x t-1 L2. 2-period lag x t-2 F. lead x
http://geocenter.github.io/StataTraining/pdf/StataCheatSheet_analysis_201615_June-REV.pdf
In this class, we are going to cover two time series approachesusing STATA software. 1 – Autoregressive Integrated Moving Average (ARIMA) Time Series Analysis 2 – Maximum Likelihood Time Series Analysis (Poisson and Negative Binomial Regression)
https://www.jrsa.org/events/presentations/western-2018/corsaro.pdf
Stata calculates 95% confidnece intervals for means and percentages. Stata will assume that any continous variable follows a normal distribution. For continuous data that are NOT normally distributed, you should either: mathematically transform the values so they take on a normal distribution, for example by taking the square root, or
http://populationsurveyanalysis.com/wp-content/uploads/2014/10/descriptive_handout.pdf
But, this approach is very limited. The new ARPOIS program package (type “net search arpois.ado”) in STATA is growing in popularity. It is a poisson regression that allows for the inclusion of autoregressive terms and overdispersion. There is some documentation online.
https://www.jrsa.org/events/presentations/western-2018/corsaro.pdf
pdf for "difference in difference analysis stata".(Page 1 of about 22 results)