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Lord, Frederic M. – 1973
Faced with a nonstandard, complicated practical problem in statistical inference, the applied statistician sometimes must use asymptotic approximations in order to compute standard errors and confidence intervals and to test hypotheses. This usually requires that he derive formulas for one or more asymptotic sampling variances (and covariances)…
Descriptors: Computer Programs, Data Processing, Error of Measurement, Hypothesis Testing
Lord, Frederic M.; Stocking, Martha – 1972
A general Computer program is described that will compute asymptotic standard errors and carry out significance tests for an endless variety of (standard and) nonstandard large-sample statistical problems, without requiring the statistician to derive asymptotic standard error formulas. The program assumes that the observations have a multinormal…
Descriptors: Bulletins, Computer Programs, Data Processing, Error of Measurement
Lord, Frederic M. – 1971
A numerical procedure is outlined for obtaining an interval estimate of a parameter in an empirical Bayes estimation problem. The case where each observed value x has a binomial distribution, conditional on a parameter zeta, is the only case considered. For each x, the parameter estimated is the expected value of zeta given x. The main purpose is…
Descriptors: Bayesian Statistics, Computer Programs, Expectation, Goodness of Fit
Lord, Frederic M. – 1971
Some stochastic approximation procedures are considered in relation to the problem of choosing a sequence of test questions to accurately estimate a given examinee's standing on a psychological dimension. Illustrations are given evaluating certain procedures in a specific context. (Author/CK)
Descriptors: Academic Ability, Adaptive Testing, Computer Programs, Difficulty Level