Update to a program for saving a model fit as a dataset



Stata Technical Bulletin

27


We can compare this to the logistic regression analysis using only the complete observations:

. keep if x”=.

. logit y x, or

Logit estimates

Log likelihood = -299.1S92S

Number of obs =

LR chi2(l)

Prob > chi2     =

Pseudo R2       =

500

92.97

0.0000
0.1345

I odd-ratio Std. Err.

z

P>z

[957, Conf.

Interval]

---------+-------------------------

x I 2.771684   .3326964

8.493

0.000

2.190638

3.506847

Note that the mean score estimate above had smaller standard error, reflecting the additional information used in the analysis.
Also, since
i is a surrogate for .r, it is not used in the complete case analysis.

Next, we consider a real example of an application of the mean score method to a case-control study of the association
between ectopic pregnancy and sexually transmitted diseases; see Reilly and Pepe (1995) for a full description of the data

. use ectopic

. meanscor y gonn-chlam,first(gonn-sexptn) second(chlam)
meanscore estimates

I

odd-ratio

Std. Err.

z

P>z

[957. Conf.

Interval]

cons

I

.4543184

.0987123

-3.631

0.000

.2967666

.6955137

gonn

I

.9495978

.2856096

-0.172

0.863

.5266531

1.712201

contr

I

.0943838

.0176643

-12.612

0.000

.0654021

.1362082

sexptn

I

2.099286

.4938943

3.152

0.002

1.323766

3.329139

chlam

I

2.471606

.7808384

2.864

0.004

1.330653

4.590858

For comparison, an analysis of complete cases only gives

. keep if chlam ~=.

. logit y gonn-chlam, or

Logit estimates

Log likelihood = -169.54627

Number of obs =
LR chi2(4)

Prob > chi2     =

Pseudo R2       =

327
104.24
0.0000
0.2351

I

odd-ratio Std. Err.

z

P>z

[957. Conf.

Interval]

— — —--— —--+—

gonn I

.7445515   .3132037

-0.701

0.483

.3264582

1.698095

contr I

.1098308   .0303352

-7.997

0.000

.063918

.1887231

sexptn I

1.93898   .7101447

1.808

0.071

.945853

3.97487

chlam I

2.47682   .7576623

2.965

0.003

1.359912

4.511054

References

Reilly, M. 1996. Optimal sampling strategies for two-stage studies. American Journal of Epidemiology 143: 92-100.

Reilly, M. and M. S. Pepe. 1995. A mean score method for missing and auxiliary covariate data in regression models. Biometrika 82: 299-314.

sg157 Predicted values calculated from linear or logistic regression models

Joanne M. Garrett, University of North Carolina, [email protected]

Abstract: The program predcalc for easily calculating predicted values and confidence intervals from linear or logistic regression
model estimates for specified values of the
X variables is introduced and illustrated.

Keywords: regression models, predicted values.

Syntax

predcalc yvar, 7yt⅛x(xvarli.st) [ level (#) model linear ]



More intriguing information

1. EU Preferential Partners in Search of New Policy Strategies for Agriculture: The Case of Citrus Sector in Trinidad and Tobago
2. The name is absent
3. WP 1 - The first part-time economy in the world. Does it work?
4. The name is absent
5. Empirically Analyzing the Impacts of U.S. Export Credit Programs on U.S. Agricultural Export Competitiveness
6. The name is absent
7. The Impact of Minimum Wages on Wage Inequality and Employment in the Formal and Informal Sector in Costa Rica
8. On Dictatorship, Economic Development and Stability
9. The Context of Sense and Sensibility
10. On Evolution of God-Seeking Mind