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In designing the private school long-term trend samples for each age, six objectives underlie the process of determining the probability of selection for each school and the number of students to be sampled from each selected school:
The goal in determining the school's measure of size is to optimize across the second to the fifth objectives in terms of maintaining the precision of estimates and the cost effectiveness of the sample design.
Therefore, to meet the target student sample size objective and achieve a reasonable compromise among the next four objectives, the following algorithm was used to assign a measure of size to each school based on its estimated age enrollment as indicated on the sampling frame.
The measures of size vary by enrollment size. The initial measures of size, \(MOS_{js}\), were set as follows: \begin{equation} MOS_{js} = PSCHWT_{s} \times PSU\_WT_{s} \times \left\{\begin{array}{llll} x_{js}{,} & \text{if } z_{js} < x_{js} \\ y_{j}{,} & \text{if } 19 < x_{js} \leq z_{js}\\ \biggl(\dfrac{y_j}{20}\biggr) \times x_{js}{,} & \text{if } 10 < x_{js} \leq 19 \\ \dfrac{y_j}{2}{,} & \text{if } x_{js} \leq 10 \\ \end{array}\right. \end{equation}
where \(PSCHWT_{s}\) is the Private School Universe Survey area frame weight for school \(s\); \(PSU\_WT_{s}\) is the PSU weight (i.e., the inverse of the PSU probability of selection) for school \(s\); \(x_{js}\) is the estimated age enrollment for school \(s\) for sample age \(j\); \(y_{j}\) is the target within-school student sample size for sample age \(j\); and \(z_{js}\) is the within-school take-all student cutoff for school \(s\) for sample age \(j\). The target within-school sample size and the within-school take-all cutoff were both 50.
Preliminary measures of size for schools not in the Honolulu PSU were set equal to the initial measures of size.
The preliminary school measure of size is rescaled to create an expected number of hits by applying a multiplicative constant \(b_{j}\), which varies by age \(j\). One can choose a value of \(b_{j}\) such that the expected overall student sample yield matches the desired target specified by the design, where the expected yield is calculated by summing the product of an individual school's probability and its student yield across all schools in the frame. For private schools, this parameter varied by private school affiliation (Catholic, non-Catholic, and unknown affiliation).
The final measure of size, \(E_{js}\), is defined as
The quantity \(u_{j}\) (the maximum number of hits allowed) in this formula is designed to put an upper bound on the burden for the sampled schools. For private schools, \(u_{j}\) is 1 because by design a school could not be selected, or hit in the sampling process more than once for a given sample age.
To address the objective in the last bullet above, an adjustment was made to the initial measures of size in an attempt to ensure the inclusion of all eligible schools that were part of the 2020 private school long-term trend sample for each age. The NAEP sampling procedures used an adaptation of the Keyfitz process to compute conditional measures of size that, by design, maximized the overlap of schools selected for both the 2020 and 2022 long-term trend assessments.
Schools were ordered within each sampling stratum using the
serpentine sort described under the
stratification of private schools. A
systematic sample was then drawn using this serpentine-sorted list and the measures of size. The numbers of private schools selected were approximately 160 for age 9 and 180 for age 13.