User Guide for the TIMSS International Database.pdf - TIMSS and ...

C H A P T E R 3 S A M P L I N G
3.7 Sampling Weights
Appropriate estimation of population characteristics based on the TIMSS samples requires that the
TIMSS sample design be taken into account in all analyses. This is accomplished in part by
assigning a weight to each respondent, where the sampling weight properly accounts for the
sample design, takes into account any stratification or disproportional sampling of subgroups, and
includes adjustments for non-response. 2
The students within each country were selected using probability sampling. This means that the
probability of each student being selected as part of the sample is known. The inverse of this
selection probability is the sampling weight. In a properly selected and weighted sample, the sum
of the weights for the sample approximates the size of the population. As is the case in TIMSS, the
sum of the sampling weights for a sample is an estimate of the size of the population of students
within the country in the sampled grades. The sampling weights must be used whenever
population estimates are required. The use of the appropriate sampling weights ensures that the
different subgroups that constitute the sample are properly and proportionally represented in the
computation of population estimates.
Tables 3.3 and 3.4 present the sample sizes and the estimate of the population size (sum of the
weights) for each participating country in Populations 1 and 2, respectively.
2 Sampling weights can only be computed when the probability of selection is known for all students.
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