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Stata 8, Programing

Hein Stigum

Presentation, data and programs at:

http://folk.uio.no/heins/

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Programing

• Programing examples– Get and use results from commands

– Automate tasks

– Define functions

– Define new commands

• Two languages– Stata Macro language For small problems

– Mata For large problem

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Stata Macro Language

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Scalar

• Scalar (numbers)scalar a=2 define

display a display content

gen x2=a*x use

• Will not work in plots

• Only numbers

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Macro

• Local Macro (number or string)local a=2 define

display `a’ display content

gen x2=`a’*x use

• Global Macro (number or string)global a=2 define

display $a display content

gen x$a=x^2 use

• Global has a “longer life” than local

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Matrix

• Matrix (matrix of numbers)matrix A=J(2,3,0) define 2*3 matrix of 0’s

matrix list A display content

matrix A[2,1]=12 change element

matrix rownames A=mean1 mean2 set names

matrix colnames A=low med high set names

Only numbersNo vectors

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Use returned resultsRun command:

Look for returned results:

Use returned results:global m=r(mean)Or put in macro:

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min w 25% 50% 75% w max

200 3180 3940 53502040 3600 5080

WeightN=583

200 53502820 3600 4280Birthweight

N=583

Example: Density plot with extra info

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Commands for previous plotRun command:

Put in macro:

Use macros:

summarize weight, detail

global N=r(N) Number of observationsglobal p10=r(p10) 10-th percentileglobal p50=r(p50)global p90=r(p90)

twoway (kdensity weight) , note(N=$N) xlabel(minmax $p10 $p50 $p90, format(%5.0f))

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Get regression resultsRun regression:

Put in matrices:

Use macros:

logistic lbw sex age

matrix b=e(b) vector of coefficients, constant lastmatrix V=e(V) variance-covariance matrixAlternative:global b1= _b[sex] sex-coefficientglobal se1=_se[sex] sex-standard error

matrix var=vecdiag(e(V)) varianceglobal ci1=exp(b[1,1]-1.96*sqrt(var[1,1])) lower CI for sex

Look for returned results:ereturn list

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Loops

• Over variables

• Over index (for-loop)

foreach var of varlist sex mage gest {summarize `var'

}

forvalues i=1(1) 5 {display `i'

}

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Loops example: Crude ORs

• Version 1

• Version 2, collect results in a matrix

foreach var of varlist sex mage gest {logistic lbw `var'

}

matrix A=J(3,3,0) local i=1foreach var of varlist sex mage gest {

logistic lbw `var'matrix A[`i',1]=exp(_b[`var'])local ++i

}

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Mata

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Mata commands

• Start and stop– mata start Mata

– end stop Mata

• Help– help mata

– help m4 intro list of functions

– help mata max() given function

Mata commands cont.

• Vectorx=(1,2,3) line vector

y=(4\5\6) column vector

x; y; y[1] display x and y and y1

z=x+y' x+y-transposed

x:+1 element by element

Differences from macro language:

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Mata commands cont.

• MatrixA=J(2,3,0) 2 by 3 matrix of 0’s

A[1,2]=14 change element

A[1,.] 1. line

A[.,1] 1. column

A[(1\3),(1,2)] submatrix: line 1 and 3, col 1 and

2

Strong syntax, direct access to all submatrices

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Mata read and set

• Read or setA=st_matrix("r(V)") 1. read from Stata

st_matrix("X",A) 2. set or reset in Stata

s=st_matrixrowstripe("r(V)") row names

m=st_global(”m") global macro

st_addvar("double",(“y", “x”)) add variables

st_store((1,n),(“y", “x”),(y1,x1)) store values

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where Stataname

Mataname

Mata commands cont.

• Run Stata commandsstata(”cmd”) run Stata commands

stata(”mean x”+strofreal(i)) mean x1

stata(”mean x”+strofreal(i)+”,detail”) mean x1, detail

Remember spaces!

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Example: plot regression results

• Ideacoeff and se as vectors,

calculate CI

store vectors as data

• Plotscatter and rcap

• Plot elements_y 1-4

_point OR or coeff

_low CI

_high CI

parity

gest10

mage

sex

-4 -3 -2 -1 0 1 2 3 4Estimates with 95% confidence intervalN=536 constant=20.77281

Logistic regression on lbw

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Example: plot valid and missing

• Ideatabstat…, stat(N)

missing relative to 1.

store vectors as data

• Plotbar, rbar,

scatter with mlabel

• Plot elements_yy 1-6

_val valid

_mis missing

_tot total

583

549

583

525

449

583

0

34

0

58

134

0birthy

gest

weight

mage

sex

id

0 100 200 300 400 500 600

Valid observations Missing observations

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Example: Bi-and multivariable table