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From |
"Nick Cox" <n.j.cox@durham.ac.uk> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: Top 10 Tricks in Stata (summary to date) |

Date |
Sun, 23 May 2004 18:32:18 +0100 |

On Friday 21 May 2004 I asked Which would we nominate as (say) the top ten tricks which are the deepest and most Stataish features in what we use? What is _both_ simple _and_ deep? What leads to great results with at most a few lines of code? ... I'd nominate straight away 1. -by:-. 2. -foreach- or -forval- with varlists or numlists. 3. -merge-. I rarely use it but -merge-masters have real leverage in file manipulations. 4. -assert-. My candidate for the most underestimated command in Stata (second is -count-). 5. -reshape-. Any other nominations? Nick n.j.cox@durham.ac.uk ============================================= Here is a compilation of responses, edited a bit. I omitted some very general comments and the most facetious suggestions. I don't think everyone was playing exactly the same game, not that it matters.... Thanks to Judith Abrams, Alan Acock, Renzo Comolli, Rafa De Hoyos, Adrian de la Garza, Peter Jepsen, SamL, Arnold Levinson. Clive Nicholas, Bill Rising, Amani Siyam, Antoine Terracol, Clint Thompson, John Wallace, Richard Williams, Fred Wolfe ============================================= -assert- (Judith Abrams, Clint Thompson) -by:- (Bill Rising, Antoine Terracol) -char- (Renzo Comolli, Bill Rising) -collapse- (Amani Siyam) -collin- (very generous amounts of well-organised output) (Clive Nicholas) -compress- (Bill Rising) -destring- (Rafa De Hoyos) -egen- (Amani Siyam, Antoine Terracol) -encode- (Clint Thompson) -encode- gets you a lot of bang for the buck: conversion of a string variable into a numeric with simultaneous labeling of the values with the original string information (John Wallace) -est table- (Clive Nicholas) comparing Stata to the competition the most useful command for me is -findit- (Alan Acock) -for- (especially the old one) (Judith Abrams) -for*- (-foreach- etc.) (Bill Rising) -generate- (Clive Nicholas) -insheet- (Clive Nicholas) -lexis- (Amani Siyam) macrolist, macros (Fred Wolfe) -margin- (very fast) (Clive Nicholas) -matrix score- (Rafa De Hoyos) -outreg- (very versatile) (Clive Nicholas) I very much like -predict-. I especially like that it can be run on something other than the estimation sample. Indeed, I sometimes temporarily wipe out the "real" data, type in some hypothetical values, run -predict-, and then restore the original data. This can be quite useful for making things like logistic regression more tangible, where it is hard to see what impact variables actually have. I also like -adjust- for similar reasons. (Richard Williams) -recode- (Bill Rising) the versatile options of -regress-, particularly -beta- and -hc3- (Clive Nicholas) -reshape- (Renzo Comolli, Amani Siyam) The fact that you can easily swap between long and wide data formats once it has been run is especially convenient, and unexpectedly useful for a lot of what I do. (John Wallace) -return list-. Or rather, all the good things stored in r(). (Peter Jepsen) -set memory-, for its optimisation in the use of resources (Rafa De Hoyos) -ssc install- (Clive Nicholas) -statsby- is my new favourite command. I almost never use -collapse- since I discovered how to use -statsby-. (John Wallace) -stset- (Peter Jepsen, Bill Rising) -sum()- (Fred Wolfe) the -svy- commands (Rafa De Hoyos) For working with complex-sample survey data (as I do all the time), the -svy- suite is Top 10 for simple syntax, flexibility (especially now that the -subpop()- option accepts -if- statements), comprehensive output and the same post-estimation approaches used for non-survey estimation programs. (Arnold Levinson) -syntax- (Bill Rising) I also very much like the -test- command and its variations. (Richard Williams) -tabulate-, particularly with use of the -all- option (Clive Nicholas) I still use -tokenize- a lot. (Antoine Terracol) -update- (Bill Rising) -update- because, with one word (i.e., simple) it allows users to easily and quickly stay abreast of the latest developments, and thus is a fundamental (i.e., deep) aspect of the continued evolution of all the other commands. (SamL) -xi:- (Clive Nicholas) _n & _N (Peter Jepsen, Antoine Terracol) all the string functions: -substr(), -trim()-, -length()-, etc. (Adrian de la Garza) treating true as 1 and false as 0 (Bill Rising) some of Scott Long's extensions for limited dependent variables have to be included as well (Alan Acock) Nick n.j.cox@durham.ac.uk > -----Original Message----- > From: owner-statalist@hsphsun2.harvard.edu > [mailto:owner-statalist@hsphsun2.harvard.edu]On Behalf Of Alan Acock > Sent: 23 May 2004 00:12 > To: statalist@hsphsun2.harvard.edu > Subject: st: Top 10 Tricks in Stata > > > Maybe it is too obvious but comparing Stata to the > competition the most > useful command for me is > findit xxxx > Some of Long's extensions for limited dependent variables have to be > included as well > > Alan Acock > acock@comcast.net > > * > * For searches and help try: > * http://www.stata.com/support/faqs/res/findit.html > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**st: Did Stata eat my variable?***From:*"Sarah A. Mustillo" <smustillo@psych.duhs.duke.edu>

**Re: st: Top 10 Tricks in Stata (summary to date)***From:*Lars Korsholm <korsholm@stat.sdu.dk>

**st: RE: Top 10 Tricks in Stata (summary to date)***From:*"Scott Merryman" <smerryman@kc.rr.com>

**Re: st: Top 10 Tricks in Stata (summary to date)***From:*Ada Ma <pec187@abdn.ac.uk>

**Re: st: Top 10 Tricks in Stata (summary to date)***From:*Richard Williams <Richard.A.Williams.5@ND.edu>

**Re: st: Top 10 Tricks in Stata (summary to date)***From:*Roger Newson <roger.newson@kcl.ac.uk>

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