TY - JOUR
T1 - A comparison of chi-squared statistics for testing homogeneity of survey data
T2 - High School and Beyond survey
AU - Wilson, Jeffrey
AU - Wilson, Patricia M.
PY - 1991/1/1
Y1 - 1991/1/1
N2 - The performance of several test statistics for comparing vectors of proportions from certain survey data was compared. The statistics were used to analyze a subsample of data from the ‘High School and Beyond’ survey. These tests include the Wald test statistic and the modified Wald test statistic Fw, the chi-squared test statistic XRSB and its modification FRSB, a test X2DMB based on a probability model, and a method of moments approach, X2H. Data were also simulated based on two-stage cluster sampling design and the type I error level, and the power of these tests was obtained for selected combinations of parameter values. The statistics X2DMB, X2RSB, FRSB and X2H performed well both for a small number of clusters or a small number of units within clusters. The power performance of these tests is quite stable. Approximate intervals were constructed for design effect constants. Methods of estimating these constants based on a normality assumption worked best.
AB - The performance of several test statistics for comparing vectors of proportions from certain survey data was compared. The statistics were used to analyze a subsample of data from the ‘High School and Beyond’ survey. These tests include the Wald test statistic and the modified Wald test statistic Fw, the chi-squared test statistic XRSB and its modification FRSB, a test X2DMB based on a probability model, and a method of moments approach, X2H. Data were also simulated based on two-stage cluster sampling design and the type I error level, and the power of these tests was obtained for selected combinations of parameter values. The statistics X2DMB, X2RSB, FRSB and X2H performed well both for a small number of clusters or a small number of units within clusters. The power performance of these tests is quite stable. Approximate intervals were constructed for design effect constants. Methods of estimating these constants based on a normality assumption worked best.
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U2 - 10.1080/02664769100000016
DO - 10.1080/02664769100000016
M3 - Article
AN - SCOPUS:84958363263
VL - 18
SP - 203
EP - 213
JO - Journal of Applied Statistics
JF - Journal of Applied Statistics
SN - 0266-4763
IS - 2
ER -