Dear Nicholas,
Thanks, yes collapse is an option but I want to
calculate means and CI for each month not for the
whole period if I use collapse then I can not use ci.
Or this is also possible?
I think that if I first create a unique value for each
month then I could be able to use e.g.
by monthnumber: ci female
so if my data looks like:
list month year female total
+-------------------------------+
| month year female total |
|-------------------------------|
1. | 1 2006 0 1 |
2. | 1 2006 0 1 |
3. | 1 2004 0 1 |
4. | 1 2006 0 1 |
5. | 1 2006 0 1 |
|-------------------------------|
6. | 1 2006 0 1 |
7. | 1 2005 0 1 |
8. | 1 2004 0 1 |
9. | 1 2005 0 1 |
10. | 1 2005 0 1 |
|-------------------------------|
11. | 1 2006 0 1 |
12. | 1 2005 0 1 |
13. | 1 2006 0 1 |
14. | 1 2004 0 1 |
15. | 1 2006 0 1 |
|-------------------------------|
and then I want to create a unique value for month per
year, so the new variable would take value of 1,2,3
according to the month and year.
this is where i get stuck:
I have tried:
1) by year month, sort: gen monthly_num=_n
this doesnt work.
and this
2)
. sort year month
. egen Monthly_num = group(month year)
this works but now I cannnot know which month
corresponds to the Monthly_num although I do get the
total number of monthsyear.
+------------------------------------------+
| month year female total Monthl~m |
|------------------------------------------|
1. | 3 2003 0 1 7 |
2. | 3 2003 0 1 7 |
3. | 3 2003 0 1 7 |
4. | 3 2003 0 1 7 |
as you see the first values of Monthly_num take=7 and
should be 1.
Anyone can help?
thanks in advance,
--- Clive Nicholas <[email protected]> wrote:
> Gaby Serdan wrote:
>
> I have data on deaths. I need to calculate the mean
> &
> CI of females in proportion to all population. Im
> trying first to create a variable for each month
> then
> take the total number of female per month and then
> divide by total number of deaths per month.
>
> [...]
>
> Im somehow lost, since my data is per individula.
> should I create a different dataset with montly
> deaths
> only or can I calculate means and confidence
> intervals
> in this same dataset.
>
>
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
>
> My suggestion would be to do the following (after
> -input-ing the data and variables that you show):
>
> . collapse (sum) female male sex_unknown, by(month
> year)
>
> The -count- variable seemed to me to be a bit of a
> red herring in getting what you wanted, so I
> dispensed with this. Since only one female appears
> in this snapshot of your data, I created
> the variable -prop- which records the monthly
> proportion of those who
> died where their sex is unknown.
>
> . g total=female+male+sex_unknown
>
> . g prop=sex_unknown/total
>
> . sum prop, detail
>
> prop
>
-------------------------------------------------------------
> Percentiles Smallest
> 1% .25 .25
> 5% .25 .5
> 10% .5 1 Obs
> 15
> 25% 1 1 Sum of Wgt.
> 15
>
> 50% 1 Mean
> .9166667
> Largest Std. Dev.
> .2249339
> 75% 1 1
> 90% 1 1 Variance
> .0505952
> 95% 1 1 Skewness
> -2.346011
> 99% 1 1 Kurtosis
> 6.82526
>
> . display .9166667-(.2249339*1.96)
>
> .47579626
>
> . display .9166667+(.2249339*1.96)
> 1.3575371
>
> I guess you'd need to define which confidence
> interval you're looking for. The percentiles don't
> look very informative, and both subtracting and
> adding 1.96 times the standard deviation to and from
> the mean (assuming a 95% CI) gives you an upper
> confidence limit above 1, which makes little sense.
> However, applying this to all of your data might
> yield more sensible statistics.
>
> Hope all that helps.
>
> Clive Nicholas
>
>
>
>
>
>
>
>
>
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