Drop command

[Ayorinde Ogunyiola]

Clyde Schechter

I will like will to create a database from an existing data for only individuals aged 16 - 65 who are employed, in labor force, have income above zero and working hours above zero or missing.

I have three variables empstat, labfroce,incwage, uhrswork

empstat which has a category for (1) N/a (2) employed (3) Unemployed and (4) Not in labor force.

labforce which has category for (1) N/A (2) No, Not in the labor force and (3) in the labor force.

will the following codes be right?

drop if age <16

drop if age >65

drop if empstat ==2| age <16

drop if empstat ==2| age >65

drop if empstat==0| age <16

drop if empstat==0| age >65

drop if empstat==3| age <16

drop if empstat==3| age >65

*Dropping labour force data

drop if labforce ==1| age <16

drop if labforce ==1| age >65

drop if incwage ==0 |age <16

drop if incwage ==0 |age >65

drop if uhrswork==0 |age <16

drop if uhrswork==0 |age >65

Clyde Schechter

[Leonardo Guizzetti]

No this isn't right. You can simplify the logic by writing inclusion/exclusion criteria in steps, since your criteria are mutually exclusive.

For example

* Restrict to working ages
keep if age >= 16 | age <= 65
* further restrict to employed
keep if empstat == 2
* further restrict to those in labour force
keep if labforce == 3
* Restrict to those with incomes above zero
keep if income > 0 & !missing(income)
* Restrict to those with positive or missing hours of work
keep if uhrswrk > 0 | missing (uhrswrk)

(Technically the condition of missing hours worked isn't necessary since Stata treats all missing values as literally larger than any non-missing value. See a discussion about this at https://www.stata.com/support/faqs/data-management/logical-expressions-and-missing-values/)

[Ayorinde Ogunyiola]

Thanks Leonardo Guizzetti

[Marcos Almeida]

The commands - drop - and - keep - have much plasticity, so to speak.

You may get the results you wish within a single line.

Please take a look at the example below:

 . sysuse auto
(1978 Automobile Data)

. sum price mpg rep78

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
       price |         74    6165.257    2949.496       3291      15906
         mpg |         74     21.2973    5.785503         12         41
       rep78 |         69    3.405797    .9899323          1          5

. keep if price < 8000 & mpg > 16 & (rep78 ==3 | rep78==5)
(43 observations deleted)

. sum price mpg rep78

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
       price |         31    4628.355    764.2687       3291       6295
         mpg |         31    23.54839    6.323705         17         41
       rep78 |         31    3.580645    .9228288          3          5

Hopefully that helps.