It is possible that you might want the percentages to be computed out of the total number of observations, and the percentage missing for each variable shown in the table. tab1 trial1 trial2 trial3 -> tabulation of trial1 Note that the percentages are computed based on the total number of non-missing cases. Like summarize, tab1 uses just available data. +-Ī second example shows how the tabulation or tab1 command handles missing data. In short, the summarize command performed the computations on all the available data. summarize trial1 trial2 trial3Īs you see in the output below, summarize computed means using 4 observations for trial1 and trial2 and 6 observations for trial3. However, the way that missing values are omitted is not always consistent across commands, so let’s take a look at some examples.įirst, let’s summarize our reaction time variables and see how Stata handles the missing values. How Stata handles missing data in Stata proceduresĪs a general rule, Stata commands that perform computations of any type handle missing data by omitting the row with the missing values. The person measuring time for that trial did not measure the response time properly therefore, the data point for the second trial is missing.
You might notice that some of the reaction times are coded using a single. We will illustrate some of the missing data properties in Stata using data from a reaction time study with eight subjects indicated by the variable id, and the subjects reaction times were measured at three time points (trial1, trial2 and trial3).
#STATA DOES NOT EQUAL SIGN HOW TO#
It will describe how to indicate missing data in your raw data files, as well as how missing data are handled in Stata logical commands and assignment statements. This module will explore missing data in Stata, focusing on numeric missing data.
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