Stata mean by group how to#

I have tried many commands but there is only a title for the California column. The two other columns do not have the titles 'Average of 38 control states' and 'P value'. The problem is that when I put mtitles ('California' 'Average of 38 control states' 'P value'), it only works for the column California as you can see in the picture. GDP per capita is measured in 1997 dollars, retail prices are measured in cents, beer consumption is measured in gallons, and cigarette sales are measured in packs') Beer consumption is averaged from 1984 to 1988. Title(Mean characteristics of California and 38 control states) ///Д¬ollabels(none) unstack noobs nonumber mtitles('California' '2' 'P value') ///ДЄddnote('All variables are averaged from 1980 to 1988. Here is the result : estpost ttest cigsale lnincome beer age15to24 retprice, by(California)Д®sttab using ta.rtf, cell('mu_1 mu_2 p') label /// The variable California is a dummy variable where 1 equals to California and 0 equals to 38 others states. I would like to create a table where the first column displays the mean characteritics of California, the second column the mean characteritics of all other states (unweighted by their population), and the last column reports the p-value of the differences in means.

Stata mean by group how to#

Now the intercept gives the mean price for domestic after controlling for length and weight and intercept plus coefficient on Foreign gives the mean price for Foreign after controlling for length and weight.Since I am a Stata beginner, I don't know how to import my data, but I just wanted some help to understand my mistake. The data looks as follows (with the correct values of avg inputed so you can see what I mean). Say, you want to control for weight and length reg price foreign weight length You need to use linear regression (again for simplicity, I am assuming linearity in all variables). # Now if you want to control other variables, there is only one way you can do that (of course there is matching which you already mentioned). If you compare two methods, you see that intercept in the first approach gives the mean price when foreign is domestic and coefficient on foreign plus the intercept gives the mean price for Foreign when foreign is Foreign. By default, mean rescales the standard weights within the over() groups. Total | 635065396 73 8699525.97 Root MSE = 2966.4 group over subpopulations defined by varlist optionally, suppress group labels. Use linear reg (for simplicity I am assuming linearity in variables) reg price foreign # without controls and if you want to find the mean of variable say price for foreign, where foreign consists of two groups (if foreign=0, domestic, and if foreign=1, it is Foreign). I was wondering if there is another way of doing this without using any matching methods but with some simple Stata commands.Д®xample illustrated with auto data in Stata Then, I calculate the mean for immigrants and similar natives.

One way to do that is using matching immigrants with natives with similar characteristics. Therefore, I have to control for the group characteristics among natives and immigrants. Hence, the difference between simple means across groups can be a result of being a immigrant but can also be because of different characteristics. immigrants are younger, less educated, etc. However, the characteristics of the two groups are different, i.e. the first one for mean group latter for pooled mean group for group A and C i get results from stata for mg and pmg for B group mg results appears whereas pmg results keep on iterating with ml log. To be more clear, let's say my groups are immigrants and natives. However, there are differences among two groups in terms of age, gender, education.

I am trying to estimate the mean of a variable for 2 different groups.