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协方差分析中的同时两两比较AI 解读

Procedures for multiple comparisons among treatment means, in analysis of covariance with a random concomitant, are considered. A Tukey-Kramer (TK)-type procedure is introduced for a conditional analysis and is compared with Thigpen and Paulson's (1974) unconditional procedure. It is first established (by simulation) that the TK procedure controls the unconditional familywise error rate at the nominal level set for the conditional procedure. In the second part of this work,…

混合线性模型中固定与随机效应估计标准误的近似AI 解读

Best linear unbiased estimators of the fixed and random effects of mixed linear models are available when the true values of the variance ratios are known. If the true values are replaced by estimated values, the mean squared errors of the estimators of the fixed and random effects increase in size. The magnitude of this increase is investigated, and a general approximation is proposed. The performance of this approximation is investigated in the context of (a) the…

概率图中若干估计量的性质AI 解读

Probability plots are popular graphical methods used to assess distributional assumptions. Under a location-scale model, the plot tends to lie on a straight line. A common practice in this situation is to fit a line through the plot and use the intercept and slope of the fitted line as estimates of the location and scale parameters. What are the properties of these estimators? Estimators from weighted least squares lines are considered, and their asymptotic, finite-sample,…

非嵌套线性模型的比较AI 解读

I consider the usual linear-model situation, except that there are two possible linear subspaces that may contain the true mean vector, and neither of the two subspaces is nested within the other. Approximate confidence intervals are developed for the difference in mean squared error (MSE) of prediction using the two models, not assuming that either model is necessarily correct. The confidence intervals are based on parametric bootstrap methods, applied to Mallows's Cp…

系统抽样中若干方差估计量的考察AI 解读

This article provides to the survey practitioner some guidance about the problem of variance estimation for equal probability single-start systematic samples. An investigation of eight alternative estimators of the variance of the sample mean is presented. In the first half of the investigation, the theoretical properties of the estimators are compared using several superpopulation models; in the second half, the comparison is empirical, based on several real populations.…

多组多维列联表的潜在结构分析AI 解读

Statistical methods are introduced for latent structure analysis of a set of two or more multidimensional contingency tables. Three basic classes of models are considered: (a) models that assume complete homogeneity across tables, (b) models that allow partial homogeneity across tables, and (c) models that allow complete heterogeneity. Methods are presented for testing whether these models are congruent with the data in the tables and for assessing the significance of…

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生物统计学：健康科学分析基础AI 解读

Introduction to Biostatistics Descriptive Statistics Some Basic Probability Concepts Probability Distributions Some Important Sampling Distributions Estimation Hypothesis Testing Analysis of Variance Simple Linear Regression and Correlation Multiple Regression and Correlation Regression Analysis - Some Additional Techniques The Chi-Square Distribution and the Analysis of Frequencies Nonparametric and Distribution-Free Statistics Vital Statistics.

生物与健康科学中的统计方法AI 解读

Descriptive methods introduction to probability and counting probability and problem solving discrete random variables continuous random variables inferences on the mean chi-squared distribution and inferences of the variance inferences on proportions comparing two means K-sample procedures - introduction to design regression and correlation categorical data some additional procedures and distribution free alternatives. Appendices: summation notation statistical tables.

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回归中的残差与影响AI 解读

Conlputat ions E.ratnple 2.3.4Jer Jiyhters no.I 2.3.3Partial residual plots Esantple 2.3.5 Jef fiyhrers no. 2 2.3.4Probability plots E.ratrtpIe 2.3.6 Cloud seeditty no. 4 2.4 Transformations 2.4.1 Fanlilies of fratlsjorr~ratiot~s 2.4.2Selectb~g a trat~s/'orrtlatiott Itr~.ariattceNor~rrality Choice c?/'trtodel i ~t t c i scalirlg the predictors It~f'erettce E.uan~ple 2.4.1 Tree data 110.I 2.4.3Diagnostic ntetttods A tkinson 's method Andrew' nterhod Application to the power…

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位置尺度回归模型的近似推断AI 解读

Abstract It is shown that χ2 and multivariate t distributions provide good approximations to posterior distributions arising in location-scale regression models. In the case of a linear regression model, Bayesian inferences based on an improper prior have conditional frequency, as well as fiducial/structural interpretation; so the results are also applicable in a non-Bayesian context. Numerical support for the approximations is presented for the case of a Weibull regression…

非嵌套线性模型的比较AI 解读

I consider the usual linear-model situation, except that there are two possible linear subspaces that may contain the true mean vector, and neither of the two subspaces is nested within the other. Approximate confidence intervals are developed for the difference in mean squared error (MSE) of prediction using the two models, not assuming that either model is necessarily correct. The confidence intervals are based on parametric bootstrap methods, applied to Mallows's Cp…

概率、随机变量与随机过程AI 解读

Part 1 Probability and Random Variables 1 The Meaning of Probability 2 The Axioms of Probability 3 Repeated Trials 4 The Concept of a Random Variable 5 Functions of One Random Variable 6 Two Random Variables 7 Sequences of Random Variables 8 Statistics Part 2 Stochastic Processes 9 General Concepts 10 Random Walk and Other Applications 11 Spectral Representation 12 Spectral Estimation 13 Mean Square Estimation 14 Entropy 15 Markov Chains 16 Markov Processes and Queueing…

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线性回归中的单侧同时界AI 解读

This article discusses the one-sided simultaneous tolerance and confidence bounds in the linear regression model. We approach the problem from the area of test theory. The bounds are constructed by projecting a region of the test statistics, and we then propose a necessary and sufficient condition for obtaining a taut tolerance bound by the method. Finally, for illustrative purposes, we give several examples of one-sided simultaneous bounds with various shapes.

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