Literaturnachweis - Detailanzeige
Autor/in | Kaufman, Steven |
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Institution | National Center for Education Statistics (ED), Washington, DC. |
Titel | 1988 Schools and Staffing Survey Sample Design and Estimation. Schools and Staffing Survey. Technical Report. |
Quelle | (1991), (85 Seiten)
PDF als Volltext |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Monographie |
Schlagwörter | Administrators; Databases; Elementary School Teachers; Elementary Secondary Education; Estimation (Mathematics); Mail Surveys; Mathematical Models; National Surveys; Private Education; Public Education; Research Design; Sampling; School Districts; School Surveys; Secondary School Teachers; Tables (Data); Teacher Supply and Demand; Schools and Staffing Survey (NCES) Datenbank; Elementary school; Teacher; Teachers; Grundschule; Volksschule; Lehrer; Lehrerin; Lehrende; Estimation; Mathematics; Schätzung; Erhebungsinstrument; Mathematical model; Mathematisches Modell; Privatunterricht; Öffentliche Erziehung; Forschungsdesign; School district; Schulbezirk; Tabelle; Lehrerbedarf |
Abstract | The Schools and Staffing Survey (SASS) represents the first time the National Center for Education Statistics has integrated three of the Elementary and Secondary Education Surveys: the Teacher Demand and Shortage Surveys, Public and Private School Surveys, and Teacher Surveys. The SASS was designed to measure the critical aspects of teacher supply and demand, the composition of teacher and administrator work force, and the general status of teaching and schooling. The SASS was conducted by the Bureau of the Census in the 1987-88 school year. The SASS sample included 12,823 public and private schools and administrators, 65,124 teachers, and 5,592 Local Education Agencies (LEAs). The merger of the three surveys produced one database to provide comparable linkage data among LEAs, schools, and teachers. Response rates ranged from 66% for private school teachers to 94.4% for public school administrators. Sample selection is discussed for public and private sectors. The discussion of estimation considers: weighting; item response rates and imputation; variance estimation; and frame evaluation. Data are reported in 18 tables. Three appendices discuss: minimizing school overlap with other national and longitudinal surveys; allocating sample groups to minimize loss of prediction for specific estimators; and the effect of a finite population correction on SASS variance estimates. (SLD) |
Erfasst von | ERIC (Education Resources Information Center), Washington, DC |