Four empirical laws of bibliometrics--anomalous number, Lotka's, Zipf's, and Bradford's--together with Laplace's "law of succession" and de Solla Price's cumulative advantage distribution are shown to be almost identical. A simple model shows that the frequency forms conform with inverse square law over appropriate interval. (Fifteen…

Two ideal-point probabilistic choice models from the external analysis of preferences are presented that allow for more flexible distributions of ideal-points. The first extends the probit model of W. Kamakura and R. Srivastava. The second is based on simplifying assumptions that lead to a multidimensional histogram of ideal-points. (SLD)

This paper makes the point that descriptive and inferential measures of nonnormality and graphic displays of the frequency distribution of important variables should be routine in research reporting. This point is particularly true for research involving measures with nonarbitrary metrics where the distribution shape is unaffected by measurement…

After discussion of the equivalency of the information laws of Bradford, Leimkuhler, Lotka, and Mandelbrot, aberrations from Leimkuhler's law (including "Groos droop" as encountered in practice) are studied. Other aberrations of Leimkuhler's law are explained, starting from generalization of verbal formulation of Bradford's Law. (18…

The normal curve has long been important in statistics. Most interval variables yield normal or quasi-normal distributions when data are collected from large samples, and the normal "Z" distribution is also used as a test statistic (e.g., to test differences between two means when sample size is large, since "t" approaches…

Estimation/smoothing methods that are flexible enough to fit a wide variety of test score distributions are reviewed: kernel method, strong true-score model-based method, and method that uses polynomial log-linear models. Applications of these methods include describing/comparing test score distributions, estimating norms, and estimating…

This Monte-Carlo study compared modified Newton (NW), expectation-maximization algorithm (EM), and minimum Cramer-von Mises distance (MD), used to estimate parameters of univariate mixtures of two components. Data sets were fixed at size 160 and manipulated by mean separation, variance ratio, component proportion, and non-normality. Results…