I know how to do this in R: e.g. pchisq(18.98, df=2, lower.tail=FALSE)
However, I've no idea about how to write Stata code to solve this problem.
In case you're interested in more general post-estimation tests check out: help test.
Otherwise is seems like chi2(2,18.98) or chi2tail(2,18.98) are what you're after (depending on what lower.tail=FALSE means.
Note that in Stata you'll probably want to put this into a "local" in order to do other things with the output.
For example if you say the following to Stata:
local pchi2 = chi2(2,18.98)
display "chi2: `pchi2'"
Stata should reply:
chi2: .9999243958967154
See for more detail and links to the Stata manual section on statistical functions:
help chi2
help chi2tail
Related
I am using National Survey Data (specifically, UK LCF) for Regression Analysis that contains a variable weighta described as following:
I really don't know which of the following Stata specifications for weighting is suitable to apply to my variable weighta. Can you please help me?
Here you can see how my the values for my weighta variable look like; they are not integer so this makes me doubt fweight specification in Stata would fit, but I am still not sure about any of the others.
weightq=quarterly weights weighta=annual weights
I have balanced panel data and my dependent variable is count one which distribution has lots of zero(0).
therefore I think it might be suitable for using negative binomial regression rather than poisson one. However, I cannot find how can I test whether xtnbreg or xtpoisson is suitable for my data.
If someone can help how can I test overdispersion to choose poisson model or nbmodel.
Thank you in advance!
In Stata, is there a way to redirect the data that a command does into a table instead of a graph?
Example: if someone created a normal probability distribution of data with the pnorm var_name command, is there a way to redirect the data so that instead of appearing in a graph, it appears in a table?
To add to #Noobie's answer:
Different commands work in different ways. There's no better short summary.
What you can look out for includes
generate() options that produce new variables. (There is absolute rule that the options have this name, but that or a similar name is the most common single variety.)
Options that allow saving results to new datasets.
Saved results, especially those visible after return list or ereturn list. These can be quite elaborate, e.g. saving of matrices of counts after tabulate.
More broadly, Stata commands aren't functions! One characteristic of a function, as so named in many languages or programs, is that there is a result, with special cases where the result is void or null. There clearly are statistical programs which in broad terms hinge on calling functions which have results, and what you see displayed is often a side-effect of that. Stata commands don't work like that in the sense that the results of a program can be various. In the case of commands designed just to show something, the "result" may be a display. It's worth noting that Mata, which underlies and underpins Stata, is more recognisably a C-like language, with (e.g.) many matrix extensions, which is based on functions (and much else).
Yes and no. It really depends on the command you are using. You should look at the help files first.
For instance, pnorm does not allow that. You can create the data yourself using the formula for pnorm described in the help file, where the cumulative distribution at some point is plotted against the so-called plotting position.
Other Stata commands allow you to generate the points directly. This is the case for kdensity for instance.
I'm trying to save output from several hundred eststo's storing results of bivariate probability models into one excel file using esttab. It works for xtlogit(both ,re and ,pa), xtprobit (both ,re and ,pa) and for the linear probability model xtreg (both standard and ,fe. However, when I use xtreg y x i.year, fe I get the error message too many base levels specified. Google doesn't help me much.
I've been trying for an hour to create a reproducible example but the stata datasets all work fine. It does not seem to be due to the number of years or the fact that different specifications have data for different years. Still, the normal xtreg, fe' works, the problem only appears with time dummies. The weirdest thing is that it works for all subsets of my variables but not for the whole list (again just the time fixed effects specifications).
Does anyone have an idea how to proceed? Using drop(*.year) works whenever the problem does not arise (so in specifications where it works, I get outputs without the year dummies) but does not prevent the too many base levels specified error; ,nobaselevels has no apparent effect as well. Is there a way to remove the time fixed effects from eststo before I pass those on to esttab? Any workaround would be appreciated as well.
The problem you might be facing is that of Stata creating different base levels for the factor variable year, in different regressions.
Try fixing the factor variable base level beforehand with fvset:
fvset base <some_number> year
Check help fvset and the manual entry for details. Also, read the source given below, which contains more information.
Source: two posts from Statalist; one from Tim Wade and another by Jeff Pitblado.
I wanted to know whether I can use the predict option for ancillary parameters (maximum likelihood ) program as follows (I estimated lnsigma and so sigma is the ancillary parameter in the model):
predict lnsigma, eq(lnsigma)
gen sigma=exp(lnsigma)
I also would like to know whether we can use above for heteroscedastic model.
Thank you in advance.
That sounds correct. I would be more explicit by typing predict lnsigma, xb eq(lnsigma). This way your code will not be broken when someone later on desides to write a prediction program for your estimation program and sets the default to something different than the linear prediction.
You can also do it in one line:
predictnl sigma = exp(xb(#2))
This assumes that lnsigma is the second equation in your model. If it is the third equation you replace xb(#2) with xb(#3). predictnl is also also an easy way of using the delta method to predict standard errors and confidence intervals for sigma.
I assume this is your own Stata program. If that is true, then you also have a third option: You can create your own prediction program, which Stata's predict command will recongnize. You can find some useful tricks on how to do that here: http://www.stata.com/help.cgi?_pred_se