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From |
"B. Timothy Walsh" <btw1@columbia.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: AW: "skipping" missing data |

Date |
Thu, 06 Aug 2009 16:49:24 -0400 |

Dear Nick,

Tim ------------------------------------------------ bysort ptnum : gen int nbobs = sum(bperwk_ < .) bysort ptnum : replace nbobs = nbobs[_N] egen newgroup = group(ptnum) if nbobs > 1 summarize newgroup, meanonly forval i = 1/`r(max)' { regress bperwk_ wk if newgroup == `i' predict p replace p1=p if newgroup == `i' drop p } --------------------------------------

Singleton panels are tagged as such by bysort ptnum : gen allonmyown = _N == 1 Alternatively, panels with two or more are tagged as such by bysort ptnum : gen twoormore = _N > 1 after which you can go egen group = group(ptnum) if !missing(bperwk_, wk) & !allonmyown OR egen group = group(ptnum) if !missing(bperwk_, wk) & twoormore B. Timothy Walsh wrote:Thank you: this worked very nicely. EXCEPT I now realize I also have instances in which there is only a single data point for an individual. Is there a simple way to modify this line? egen group = group(ptnum) if !missing(bperwk_, wk)> --On Thursday, August 06, 2009 11:28 AM -0500 Nick CoxHere is one of several alternatives. generate p1=. egen group = group(ptnum) if !missing(bperwk_, wk) summarize group, meanonly forval i = 1/`r(max)' { regress bperwk_ wk if group == `i' predict p replace p1=p if group == `i' drop p } That sets the missings on one side. See also: FAQ . . . . . . . . . . Making foreach go through all values of a variable . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . N. J. Cox 8/05 Is there a way to tell Stata to try all values of a particular variable in a foreach statement without specifying them? http://www.stata.com/support/faqs/data/foreach.html Despite the reference to -foreach- the FAQ is still pertinent. Nick Martin Weiss wrote:************* capture ************* You could put it in front of individual commands, or the entire -forvalues- loop.B. Timothy WalshI am attempting to generate predictions from regressions performed for each of a longish list of individuals. The problem is that, for some individuals, there are no dependent variable data (entries are missing), so the regression attempt fails. The problem is that the forvalues loop then exits. I would like to somehow "skip" these individuals. Loop seems to work fine if there are enough data to perform a regression. I'd be grateful for any suggestions. Here's the code: generate p1=. forvalues i = 1/50 { //50 individuals regress bperwk_ wk if ptnum == `i' predict p replace p1=p if ptnum == `i' drop p } I'm pretty much a Stata novice. So, I apologize if I am missing something obvious. Using version 10.1.* * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

* * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: AW: "skipping" missing data***From:*Nick Cox <n.j.cox@stata.com>

**References**:**st: "skipping" missing data***From:*"B. Timothy Walsh" <btw1@columbia.edu>

**st: AW: "skipping" missing data***From:*"Martin Weiss" <martin.weiss1@gmx.de>

**Re: st: AW: "skipping" missing data***From:*Nick Cox <n.j.cox@stata.com>

**Re: st: AW: "skipping" missing data***From:*"B. Timothy Walsh" <btw1@columbia.edu>

**Re: st: AW: "skipping" missing data***From:*Nick Cox <n.j.cox@stata.com>

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