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

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

Subject |
RE: st: Regressing with variables with missing values |

Date |
Sun, 6 Nov 2005 23:41:26 -0000 |

I repeat my profession of ignorance and my advice to study the syntax more carefully. I'd also get hold of Patrick's articles. Nick n.j.cox@durham.ac.uk Ramani Gunatilaka > Nick, > Thanks, that worked. I should say, though, that I have several > variables with missing values and I tried ice with all of them and it > didn't work, so then I tried with just one. > See, this is what happens: > > . /*MICE to impute missing values*/ > . use uphvar02, clear > > . ice incdisCh incdisCity indy02 workhrs happy r_health edyrs ln_pcy02 > ln_avcityy city province male di > > vorced widowed finassets hhdebt using uricevar02, > eq(incdisCh: indy02 ln_pcy02 ln_avcityy city provin > > ce finassets hhdebt, incdisCity: indy02 ln_pcy02 ln_avcityy > city province finassets hhdebt, happy: ln > > _pcy02 r_health male divorced widowed) genmiss(M1) id(flag1) replace > > Variable | Command | Prediction equation > -------------+-------------+---------------------------------- > ---------------- > incdisCh | mlogit | indy02 ln_pcy02 ln_avcityy city province > | | finassets hhdebt > incdisCity | mlogit | indy02 ln_pcy02 ln_avcityy city province > | | finassets hhdebt > indy02 | regress | incdisCh incdisCity workhrs > happy r_health edyrs > | | ln_pcy02 ln_avcityy city > province male divorced > | | widowed finassets hhdebt > workhrs | regress | incdisCh incdisCity indy02 happy > r_health edyrs > | | ln_pcy02 ln_avcityy city > province male divorced > | | widowed finassets hhdebt > happy | mlogit | ln_pcy02 r_health male divorced widowed > r_health | | [No missing data in estimation sample] > edyrs | | [No missing data in estimation sample] > ln_pcy02 | | [No missing data in estimation sample] > ln_avcityy | | [No missing data in estimation sample] > city | | [No missing data in estimation sample] > province | | [No missing data in estimation sample] > male | | [No missing data in estimation sample] > divorced | | [No missing data in estimation sample] > widowed | | [No missing data in estimation sample] > finassets | | [No missing data in estimation sample] > hhdebt | | [No missing data in estimation sample] > > Imputing 1..file uricevar02.dta saved > > . sort city province hhid > > . compress > > . save uricevar02, replace > file uricevar02.dta saved > > . > . > end of do-file > > . count if happy==. > 65 > > > Would you have any ideas about what's going wrong? I'd be > very grateful. > Thanks so much, > Ramani > > On 07/11/05, Nick Cox <n.j.cox@durham.ac.uk> wrote: > > I've not used -ice- myself: I just recommend it! > > > > However, a quick glance suggests that you > > are misunderstanding the syntax. It may be > > that what you want is something more like > > > > uvis regress happy ln_pcy02 r_health male divorced widowed, > > gen(HAPPY) > > > > Nick > > n.j.cox@durham.ac.uk > > > > Ramani Gunatilaka > > > > > I have been following up on all the useful comments I got and have > > > been working on that ice thing to replace missing values. > > > Unfortunately the programme goes through the motions but doesn't > > > replace any missing values. I am at my wit's end. The dependent > > > variable and the one that has missing values is happy > (which takes the > > > values 1-5 depending on level of happiness (the data set > as a whole > > > has 6805 observations), and my code runs like this. > > > > > > use uphvar02, clear > > > > > > . ice happy ln_pcy02 r_health male divorced widowed using > uricevar02, > > > cmd(regress) eq(happy: ln_pcy02 r _health male divorced widowed) > > > genmiss(M1) id(flag1) replace > > > > > > This is my output: > > > > > > Variable | Command | Prediction equation > > > -------------+-------------+---------------------------------- > > > ---------------- > > > happy | regress | ln_pcy02 r_health male > divorced widowed > > > ln_pcy02 | regress | [No missing data in > estimation sample] > > > r_health | regress | [No missing data in > estimation sample] > > > male | regress | [No missing data in > estimation sample] > > > divorced | regress | [No missing data in > estimation sample] > > > widowed | regress | [No missing data in > estimation sample] > > > > > > Imputing > > > [Only 1 variable to be imputed, therefore no cycling needed.] > > > 1..file uricevar02.dta saved > > > > > > . sort city province hhid > > > > > > . compress > > > > > > . save uricevar02, replace > > > file uricevar02.dta saved. > > > end of do-file > > > > > > But when I check - here's what I get. Missing values still there. > > > > > > . count if happy==. > > > 65 > > > > > > Does anybody have any ideas as to what might be going wrong? * * 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/

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