Computing for Research I Spring 2011

1. Computing for Research ISpring 2011 Stata Programming February 21 Primary Instructor: Elizabeth Garrett-Mayer

2. Some simple programming • Once again, princeton’s site has some great easy info: http://data.princeton.edu/stata/programming.aspx • We will discuss a few things: • ‘macros’ • looping • writing commands • We will not discuss ‘mata’: powerful matrix programming language

3. macros • macro = a name associated with some text. • macros can be local or global in scope. • Example of use: shorthand for repeated phrase • graphics title • set of ‘adjustment’ covariates

4. Example: covariates * use SCBC data use "I:\Classes\StatComputingI\SCBC2004.dta", clear * make tumor numeric and transform gen sizen=real(tumor) gen logsize = log(sizen) replace logsize = . if sizen==999 regress logsize age black graden *define local macro local adjusters age black graden regress logsize `adjusters' regress logsize `adjusters' i.ercat regress logsize `adjusters' i.prcat regress logsize `adjusters' i.ercati.prcat NOTE: must use accent (`) in upper left of keyboard as beginning quote and apostrophe (‘) (next to enter key) for end quote.

5. Example: titles * another example infile str14 country setting effort change /// using http://data.princeton.edu/wws509/datasets/effort.raw, clear graph twoway (lfitci change setting) /// (scatter change setting) /// , title("Fertility Decline by Social Setting") /// ytitle("Fertility Decline") /// legend(ring(0) pos(5) order(2 "linear fit" 1 "95% CI")) local gtitles title("Fertility Decline by Social Setting") ytitle("Fertility Decline") * with macro graph twoway (lfitci change setting) /// (scatter change setting) /// , `gtitles' legend(ring(0) pos(5) order(2 "linear fit" 1 "95% CI")) * without macro graph twoway (lfitci change setting) /// (scatter change setting) /// , legend(ring(0) pos(5) order(2 "linear fit" 1 "95% CI"))

6. Storing results * run regression and store r-squared value regress change setting local rsq = e(r2) display rsq * run new regression regress change setting effort display e(r2) see old saved r-squared display rsq * still there!

7. Global macros • Global macros have names of up to 32 characters and, as the name indicates, have global scope. • You define a global macro using global name [=] text and evaluate it using $name. (You may need to use ${name} to clarify where the name ends.) • “I suggest you avoid global macros because of the potential for name conflicts.” • A useful application, however, is to map the function keys on your keyboard. If you work on a shared network folder with a long name try something like this

8. More on macros • Macros can also be used to obtain and store information about the system or the variables in your dataset using extended macro functions. • For example you can retrieve variable and value labels, a feature that can come handy in programming. • There are also commands to manage your collection of macros, including macro list and macro drop. Type help macro to learn more.

9. Looping • foreach: loops over a set of variables • forvalues: loops over a set of values (index) • Also: • while loops • if and else sets of commands

10. Programming • ‘ado’ files • create commands in ado file and put them in the appropriate directory for Stata to find • Can also create them in do files for local use • See • http://data.princeton.edu/stata/programming.aspx • www.ssc.upenn.edu/scg/stata/stata-programming-1.ppt