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
[email protected]
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 <[email protected]> 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
> > [email protected]
> >
> > 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?
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