TRAINING KEY 101a: Regression Estimation

Practical Methods for Design and Analysis of Complex Surveys.
Risto Lehtonen and Erkki Pahkinen

TRAINING KEY 101a: Regression Estimation



INTRODUCTION

We will first show in point A how to compute regression estimated totals with their standard error estimates. In point B, regression estimation of totals can be examined in more detail by selecting different SRSWOR samples (simple random sampling without replacement) and comparing the results. In point C, you can download a piece of SAS code for your own further training. Regression-estimated totals will be computed in the Province'91 Population for UE91 (the number of unemployed in a county in 1991). The auxiliary variables to be used are HOU85 (the number of households according to population census 1985) and URB85 (indicator of urban municipalities).



A) REFERENCE EXAMPLE 3.13: SAS CODE AND OUTPUT

Computation of a regression estimated total and its standard error for UE91. SAS code and output will be examined for two cases:
 

One auxiliary variable (HOU85)
Two auxiliary variables (HOU85 and URB85)


B) REGRESSION ESTIMATION WITH DIFFERENT SRSWOR SAMPLES

Examination of the variation of total estimates of UE91 calculated from different pre-drawn SRSWOR samples using auxiliary variable HOU85. Instructions will be given once you start.
 

 


C) INTERACTIVE SAS USE

Please download the SAS code for your own further training. Select your own sample or several samples and exercise regression estimation with different sample sizes for a SRSWOR sample. The macro parameters used in the application are n = sample size (default=8) and seed = seed for the random number generator (default seed=01234567). You may choose 2< n < 32 (recommendation n ? 4) elements in the sample and by changing the seed different sample configuration will be obtained.

NOTE! You need to have access to SAS in your computer.
 

  Macro using SAS/SURVEYREG procedure
  Macro using Formula (3.32)