Advanced Stata Skills

Transcription

1 Advanced Stata Skills Contents Stata output in Excel & Word... 2 Copy as Table... 2 putexcel... 2 tabout (v3)... 2 estout / esttab... 2 Common Options... 2 Nice Looking Tables in Stata... 3 Descriptive Statistics... 3 Table of Statistics... 3 Less Good Alternatives... 4 Formatting Regression Output... 5 Storing Results... 5 estimates... 5 estout... 5 outreg Common Options... 5 Margins... 6 Running the Regression... 6 Predictions... 6 Plots... 6 Unspecified Variables... 7 Specifying Values... 7 Matrix Operations... 8 Basic Operations... 8 Example: Regression Output... 8 Example: Multiple T-Tests... 8 Macro Variables & Loops... 9 Example: Appending many files... 9 Example: Identifying variables in file... 10

2 Stata output in Excel & Word In excel, the functions can overwrite the cells you have if you use the new XLS[X] functions (only in tabout v3 available on the website only). You can set up a table how you want referencing those cells. Note that tabout puts in numbers as text, so if you need to do additional formatting, you have to change back to number (e.g., numbervalue()) Copy as Table With output selected, right click and choose Copy Table. This does not have any special powers to split output into a table, it simply looks for vertical and horizontal breaks. It is usually best to copy tables to Excel before copying to word as needed. putexcel (built-in command) don t forget to set a working directory first so that it goes in the right spot. Must always specify the exact cell (or upper left cell) to put things tabout (v3) Typically the best option for tables. can change style to docx (and file extension) to go straight to word. To install the vry latest version (e.g., v3): Run this to determine which directory to put your ado files: adopath Go to tabout s webpage and download the program file for your version of Stata. Save the file with the extension.ado in the directory listed as PERSONAL above which tabout To install v2, or once v3 becomes the official version (not as of ) ssc install tabout estout / esttab ssc install estout after installing, see help estout Very versatile, so basic things can sometimes be difficult. Common Options specify option: append/modify or replace specify option location(1 2) (row 1, col 2/B) specify opction c : freq

3 Nice Looking Tables in Stata Descriptive Statistics sysuse auto, clear command varlist qualifiers using file, options ssc install tabout Frequency Tables Original tab1 rep78 foreign Tabulate Summarize Original tab foreign, sum(mpg) tabout rep78 foreign using xttab1, c(freq col cum) style(docx) clab(freq. Percent Cum.) replace tabout foreign using xttabsum, sum c(mean mpg sd mpg N mpg) clab(x sd n) style(docx) replace Pivot Table (1 var) Original tab rep78 foreign, sum(mpg) nost nofreq 2-way Table Original tab rep78 foreign, col Table of Statistics tabout rep78 foreign using xtpivot, sum c(mean mpg) clab(x) style(xlsx) tabout rep78 foreign using xttab2.xlsx, c(freq col) style(xlsx) // statistics are side-by-side, not vertical ssc install estout Summarize Original tabstat price mpg rep78, by(foreign) statistics(mean sd) columns(statistics) estpost tabstat price mpg rep78, by(foreign) statistics(mean sd) columns(statistics) listwise esttab. using tabstat_1.rtf, cells("mean(fmt(a3)) sd") Original summarize price mpg rep78 Correlation estpost summarize price mpg rep78 esttab. using sum1.tab, cells("mean sd count") noobs tab label replace Original pwcorr price mpg turn foreign, star(.05) T-test Original ttest price, by(foreign) estpost correlate price mpg turn foreign, matrix esttab. using corr1.tab, not unstack compress noobs tab replace label p estpost ttest price mpg headroom trunk, by(foreign) // can do multiple at the same time esttab., wide

4 Less Good Alternatives Pivot table (2+ statistics) 2-way Table Correlation Table of Statistics Stata option, but no good alt alt alt table foreign rep78, c(mean mpg sd mpg N mpg) cap erase xtpivot2.tab levelsof foreign, local(levels) foreach t of local levels { tabout rep78 if foreign == `t' using xtpivot2.tab, h1(miles per Gallon) sum c(mean mpg sd mpg N mpg) clab(x sd n) style(tab) append } estpost tabulate rep78 foreign esttab. using xttab2.tab, c(b colpct) tab replace unstack nonumber noobs nomtitle collabels(none) * Does not display labels for summary statistic or variable label for either variable net install makematrix makematrix mycorrs, from(r(rho)) cols(mpg) format(%9.2f): pwcorr price mpg turn foreign putexcel set corr3 putexcel A1 = matrix(mycorrs), names * cols(mpg) allows to limit to the correlates of one variable estpost tabstat price mpg rep78, by(foreign) statistics(mean sd) columns(variables) listwise matrix(transpose) esttab. using tabstat_2.rtf, main(mean) aux(sd) nostar unstack noobs nonote label Summarize alt tabstat with the save option and putexcel

5 Formatting Regression Output For unformatted statistics, see Matrix Operations Storing Results After you run each regression model, run estimates store with a brief label for that model. Giving the same name with update/overwrite the results. You can then specify specific models to include or use all saved models with * (can sometimes leave blank). etc. estimates clear (or just be careful with names) reg estimates store full reg estimates store partial estimates Built-in to stata estimates table * estout If you want to store the results using a prefix command (so it is all on one linne, use eststo full: reg rtf does the best because the special characters (brackets, parenthese, get lost when opening other formats in Excel. esttab * using output.rtf, ci(2) noconstant wide label nonumbers b(%6.2f) noisily esttab * using output.rtf, cells(`" b(fmt(a2) star) ci(par("[ " " - " " ]"))" ) noconstant wide label nonumbers b(%6.2f) esttab using output.rtf, wide label nonumbers b(%6.2f) outreg2 outreg2 has been around longer (previously outreg), so it tends to be more popular. However, estout is often more flexible. It can can be implemented very similarly. after installing, see help outreg2 ssc install outreg2 example: outreg2 [*] using outtest, word eform label bdec(2) sideway stats(coef ci) ci bracket(ci) nocons Common Options eform specifies to use the coefficient as displaed (e.g., odds-ratios if odds-ratios), so it is important for logistic regression. replace specifies to overwrite the file if it already exists, usually good so you can replicate.

6 Margins From your regression results, you should be able to calculate the predicted value of the DV for different values of each IV. But, Stata can also do this for you. For logistic regression, Stata even converts the predictions to actual probabilities so they are much easier to understand. Running the Regression When running the regression, be sure to use factor variables (i. and c.) as necessary, or margins will not treat the variables properly. Assumes all variables are continuous except when using the interaction symbol (assumes factor). You can ask for margins for the interaction, just express it the same way female#black (without the factor variable indications or the individual effects, unless you want them too. regress price mpg turn i.foreign logistic foreign price mpg turn logistic score i.class example class -> 0 = no class, 1 = took class logit price mpg Predictions Average Adjusted Predictions AAP. See Default. Predictions are made for the specific cases in yourdataset, whatever the values may be. margins foreign, at( turn = 40 mpg = ( ) ) over(rep78) atmeans with multiple IVs, this can be combined with at() and other specifying Plots marginsplot accepts all the other normal graphing commands. See graph twoway marginsplot, x(read)

7 Type Command Explanation When to use Unspecified Variables both margins Stata uses the cases you have, acting as if each case has the values you specify and their original values on all other variables. But, because it doesn t change any other values, if the categories are related to the values of other variables, it is weird (you are acting as if a female was a male). both margins, atmeans Predicts with categorical dummy codes at the observed proportion, and neither 0 nor 1. e.g.,.70 (for when 70% of the cases have a 1) instead of 0 or 1. Predicts with numeric variables at theiir mean value. This can be useful because you can state exactly what value of each variable the predictions were calculated for. categorical margins, asbalanced Assumes all categories in the factor variables are eqully likely (e.g., the groups are equal size/proportions). Adjusts the predictions as if your dataset had equal. Specifying Values categorical margins class Predicts for each level of class Default To account for different likelihood of group memberships. If a case with all the values at the mean is a reasonable representation of a typical case. To correct for category inbalance in your data, which is equal in the population.. both margins, at( class = ( 0 1 ) ) Predicts for the specified levels of class. To predict for only certain values. margins, at( mpg = ( ) ) margins, at( mpg = (20(01)40) ) (these are identical) Using the dataset as is, calculates the average DV if each observation had the specified values. categorical margins, over(class) Tweaks the default method of setting values for unspecified variables. Uses only cases with each particular value of over. both margins, dydx(class) Calculates the marginal effect (partial effect) for that variable. For a linear regression this is the same as the coefficient. margins, dydx(mpg) If members of each group do differ on other characteristics. To get logistic regression dummy coefficients as probabilities. For logistic regression to report one number.

8 Matrix Operations Basic Operations matrix name = expression matrix a = (1\ 2\ 3) // creates one column matrix b = (1, 2, 3) // creates one row matrix c = (1,2\3,4\5,6) // creates a 2 column, 3 row matrix matrix list c // print the matrix matrix d = c // transpose c to make a 3 column, 2 row matrix matrix e = c[2..3,.] // extract the 2nd and 3rd row of c (3,4\5,6) matrix f = J(2,3,.) // create a 2 row, 3 column matrix with all missing values matrix g = ( nullmat(g) \ 2 ) // nullmat() create matrix g if doesn t exist, useful for loops matrix f = g \ J(2,2,.) // add 2 blank rows to the 3x2 matrix xxx Example: Regression Output regress price mpg headroom trunk matrix reg = r(table)' putexcel set "regtable.xlsx", modify putexcel A1=matrix(reg), names Example: Multiple T-Tests cap matrix drop ps foreach i in { qui ttest pwfa if periods == `i', by( wfa841_12mo ) matrix ps = ( nullmat(ps) \ `r(p)', `i' ) } // end foreach matrix list ps, format(%5.4f) putexcel set mytable putexcel A1 = matrix(ps), names putexcel B1 = (e(n)) C1 = ( Obs )

9 Macro Variables & Loops Stata Syntax: Loops for Appending CSV Files see also: help extended_fcn Assumes files are in the subfolder csv Local variables are marked by a backtick (`) and a single quote ( ): `var' Example: Appending many files /****** ALL-IN-ONE ******/ cd "C:\myfolder" clear /**** STEP-BY-STEP *****/ cd "C:\myfolder" mkdir "stata" clear local csvfiles: dir "csv" files "*.csv" foreach file of local csvfiles { preserve insheet using csv/`file', clear ** add syntax here to run on each file** save temp, replace restore append using temp } rm temp // remove temporary.dta file save alldata, replace local csvfiles : dir "csv" files "*.csv" foreach file of local csvfiles { insheet using csv/`file', clear local name : subinstr local file ".csv" "" gen file = `name' // optional ** add syntax here to run on each file ** save stata/`name'.dta, replace } cd "stata" local statafiles : dir. files "*.dta" append using `statafiles' cd.. save alldata, replace

10 Example: Identifying variables in file If you only want a specific list of variables, that some files do not have. * Remember that local only lasts through the run you are doing. * YOU CANNOT RUN ONE LINE AT A TIME How to get a list of only those variables shared by two lists: local want id1 id2 id3 id4 id5 di "`want'" unab have: _all di "`have'" local tokeep: list want & have di "`tokeep " keep `tokeep Example also shows when the datafiles are in multiple directories. cd "C:\myfolder" clear local want id1 id2 id3 id4 id5 local dirs: dir "Countries" dirs "*" foreach dir of local dirs { local files: dir "`dir " files "*.dta" foreach file of local files { preserve use Countries/`dir /`file', clear ** add syntax here to run on each file** unab have: _all local tokeep: list want & have keep `tokeep } } save temp, replace restore append using temp rm temp // remove temporary.dta file save alldata, replace