sysuse nlsw88, clear
tabout age south race collgrad over(union) using table2.txt
How can it be possible to do tabout in Stata when you have continuous (such as age) and categorical (such as south and race and collgrad) variables?
please explain your desired outcome, you could just run the following
tabout age south race collgrad union using table2.txt
Related
I am getting error in Stata by using the following commands:
gen daily=date( Date,"MDY")
tsset daily
rolling cent=r(c_1), window(#) clear: centile lnreturn, centile(5)
but this is not giving me the result.
Your syntax looks legal apart from the use of #. Here is a different example that works:
webuse grunfeld, clear
tsset company year
rolling cent=r(c_1), window(7) clear: centile invest, centile(5)
I want to create in Stata a coefplot variable: however, in one of the models I want to show there is no value for the estimate which I report, but instead I want to report the constant.
How is that possible?
sysuse auto, clear
regress price weight
coefplot, drop(weight) rename(_cons = abcdef)
I am trying to tabulate frequencies for a variable divided in two groups. That is, I would like to see how much a variable takes value "Yes" divided by both region and sex. Now, this is easy to do in Stata using "tab" and option row, but I have trouble exporting it. To make it clear, I am able to build the table with absolute frequencies in this way:
eststo formalyes: estpost tab regionwb_c female if fin22a==1
eststo formalno: estpost tab regionwb_c female if fin22a==0
eststo formalt: estpost tab regionwb_c female
estout formalyes formalno formalt using summformal.tex, replace varlabels(`e(labels)') unstack booktabs ///
mgroups("Yes" "No" "Tot", pattern(1 1 1) prefix(\multicolumn{#span}{c}{) suffix(}) span erepeat(\cmidrule(lr){#span})) fragment
This, put in my latex code, produces this relatively nice table:table1
Now what I would like to do is to reproduce the exact same table, but to have the relative and not absolute frequencies there. Now normally to my understanding if you want the relative frequencies you can have
tab x y, row nofreq
but if you try to combine this with estpost it does not work. Are there any hints? I tried working it out with tabout, but all i was able to produce is this:
tabout regionwb_c female using trial.tex, replace percent style(tex) c(mean fin22a) sum
Which gives this:table2
Where, as you can see, I am pretty lost. I am sorry if the question sounds silly but I struggled finding results online or on the tabout manual. I hope somebody can help me.
I have not worked with tabout before, but maybe one way to work around it could be to just program new variables containing the male and female relative frequencies by regionwb_c using the egen command for example (like in this link enter link description here. Then you could just pass these relative frequencies variables in your table.
Could that maybe help you? Good Luck!
I'm doing an analysis of the Current Population Survey. I have a wage variable (wage), a time-series variable (qtr), and an observational weight (pworwgt). Each quarter has thousands of observations.
I can easily make a table showing the weighted average wage in each quarter:
table qtr [iw=pworwgt], contents(mean wage)
What I want to do, however, is graph this easily within Stata. I tried to use egen to make a variable containing the mean by qtr, but egen mean() does not allow for weights.
One of the many ways this can be done is with a regression followed by two margins* commands:
webuse hanley
table rating [iw=pop], contents(mean disease)
reg disease i.rating [iw=pop]
margins rating
marginsplot, noci
This has the advantage of not altering your data in any way.
I want to create a table in Stata with the estout package to show the mean of a variable split by 2 groups (year and binary indicator) in an efficient way.
I found a solution, which is to split the main variable cash_at into 2 groups by hand through the generation of new variables, e.g. cash_at1 and cash_at2. Then, I can generate summary statistics with tabstat and get output with esttab.
estpost tabstat cash_at1 cash_at2, stat(mean) by(year)
esttab, cells("cash_at1 cash_at2")
Link to current result: http://imgur.com/2QytUz0
However, I'd prefer a horizontal table (e.g. year on the x axis) and a way to do it without splitting the groups by hand - is there a way to do so?
My preference in these cases is for year to be in rows and the statistic (e.g. mean) in the columns, but if you want to do it the other way around, there should be no problem.
For a table like the one you want it suffices to have the binary variable you already mention (which I name flag) and appropriate labeling. You can use the built-in table command:
clear all
set more off
* Create example data
set seed 8642
set obs 40
egen year = seq(), from(1985) to (2005) block(4)
gen cash = floor(runiform()*500)
gen flag = round(runiform())
list, sepby(year)
* Define labels
label define lflag 0 "cash0" 1 "cash1"
label values flag lflag
* Table
table flag year, contents(mean cash)
In general, for tables, apart from the estout module you may want to consider also the user-written command tabout. Run ssc describe tabout for more information.
On the other hand, it's not clear what you mean by "splitting groups by hand". You show no code for this operation, but as long as it's general enough for your purposes (and practical) I think you should allow for it. The code might not be as elegant as you wish but if it's doing what it's supposed to, I think it's alright. For example:
clear all
set more off
set seed 8642
set obs 40
* Create example data
egen year = seq(), from(1985) to (2005) block(4)
gen cash = floor(runiform()*500)
gen flag = round(runiform())
* Data management
gen cash0 = cash if flag == 0
gen cash1 = cash if flag == 1
* Table
estpost tabstat cash*, stat(mean) by(year)
esttab, cells("cash0 cash1")
can be used for a table like the one you give in your original post. It's true you have two extra lines and variables, but they may be harmless. I agree with the idea that in general, efficiency is something you worry about once your program is behaving appropriately; unless of course, the lack of it prevents you from reaching that state.