Figure 1(a) shows a random sampling plan on a surface where each point on the surface had an equal chance of being selected. In the case of random-sampling the n sample sites are selected so that each member of the population has an equal and independent chance of selection. population for details on the representativeness of the sample, see the CAS Interpretive Handbook ( Naglieri & Das, 1997b). The methods used to collect the data were designed to yield high-quality data on a sample that closely represents the U.S. The CAS standardization sample was stratified on the basis of Age (5 years 0 months through 17 years 11 months) Gender (Female, Male) Race (Black, White, Asian, Native American, Other) Hispanic origin (Hispanic, Non-Hispanic) Region (Midwest, Northeast, South, West) Community Setting (Urban/Suburban, Rural) Classroom Placement (Full-Time Regular Classroom, Part-Time Special Education Resource, Full-Time Self-Contained Special Education) Educational Classification (Learning Disability, Speech/Language Impairment, Social-Emotional Disability, Mental Retardation, Giftedness, and Non-Special Education) and Parental Educational Attainment Level (less than high school degree, high school graduate or equivalent, some college or technical school, four or more years of college). A group of achievement tests was also administered to a 1600-person subsample of the 2200-person standardization group. Of that sample, 2200 children made up the normative sample and an additional 872 children participated in reliability and validity studies. During the standardization and validity study data-collection program, the CAS was administered to a total of 3072 children. Children from both regular education and special education settings were included. The CAS was standardized for children aged 5–17 years, using a stratified random sampling plan that resulted in a sample that closely matches the U.S. NAGLIERI, in Handbook of Psychoeducational Assessment, 2001 Standardization The Das–Naglieri Cognitive Assessment System in Theory and Practice Randomized samples will most likely be more representative on uncontrolled factors than an equivalent quota sample. That is, while a quota sample will be representative of the population on the variables used to define the strata, it may not be on other variables. Second, because the observations included in a quota sample are selected nonrandomly, this may introduce bias into the sample that a random sample would not. First, because the selection of sampling units is non-random, the usual sampling error formulas (such as the estimation of variances on our estimated parameters) cannot be applied to the results of quota samples with any confidence. Quota sampling is generally less desirable than stratified random sampling for two reasons. Subjects for the interviews are selected based on convenience and the judgement of the interviewer. For instance, if a population is known to be 70% men and 30% women, a survey of 100 people using quota sampling would ensure that 70 of the interviews were with men and 30 were with women. A quota is set for each stratum of n h observations, and the researcher continues sampling until the quota for each stratum is filled. For a fixed sample size n, the n h required in each stratum for proportional stratification is determined. Like stratified random sampling, the population is first divided into strata. Quota sampling is the nonprobability equivalent of stratified random sampling. Garrett Glasgow, in Encyclopedia of Social Measurement, 2005 Quota Sampling
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