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致癌性死因检验中的误分类调整AI 解读

The cause-of-death test (Peto 1974; Peto et al. 1980) provides a test for carcinogenicity without requiring extreme lethality assumptions. The approach has been criticized, however, because cause-of-death determinations require subjective decisions by pathologists and may be unreliable. Using a missing data formulation, we derive a simple, intuitive modification of the test that allows for misclassification of cause of death. The modified statistic is a function of the…

信息性删失模型AI 解读

In the usual model for censored survival analysis, observations are of the form X = min(T, C), where T and C are nonnegative random variables representing lifetime and censoring time, respectively. Under the usual assumption of independence of T and C, the Kaplan-Meier estimator (KME) is the appropriate estimator of S(t) = Pr(T > t). The KME can lead to substantial overestimates of survival probabilities if the event of censoring indicates an unfavorable prognosis for future…

贝叶斯决策程序在遗传连锁推断中的应用AI 解读

The purpose of this article is to introduce the concept of O-Ki loss to the inference of genetic linkage. The prior information proposed by Elston and Lange (1975) was used. To help geneticists to understand the implications of the loss function and the Bayes decision rule, the Bayes decision procedure proposed in this article was suggested to be treated as a conventional test statistic. Then it seems almost natural to compare the performance of power of the statistic…

统计信息与似然：批判性论文集AI 解读

I Information and Likelihood.- I Recovery of Ancillary Information.- 0. Notes.- 1. Introduction.- 2. The Sample Size Analogy.- 3. A Logical Difficulty.- 4. Conceptual Statistical Experiments.- II Statistical Information and Likelihood Part I: Principles.- 0. Notes.- 1. Statistical Information.- 2. Basic Definitions and Relations.- 3. Some Principles of Inference.- 4. Information as a Function.- 5. Fisher Information.- 6. The Likelihood Principle.- III Statistical Information…

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多项逻辑回归相对于有序逻辑回归的分类效率AI 解读

Classification procedures are useful for the prediction of a response (or outcome) as a result of knowledge of the levels of one or more independent (or predictor) variables. The procedure is said to classify the (possibly multivariate) observation to a level of the response variable. An example might be the prediction of whether an individual will be well, suffer a nonfatal heart attack, or suffer a fatal heart attack. This prediction might be made on the basis of the…

利用独立性结构改进列联表概率估计AI 解读

Estimation of the cell probabilities in a two-way contingency table is considered when it is plausible that the table might have an independence structure relating to the two traits. In a classical nonparametric setup, the unrestricted maximum likelihood estimators of the cell probabilities are the corresponding sample proportions; under the assumption of independence, the restricted estimators are the product of the respective row and column sample proportions. The latter…

正值随机变量尺度的渐近极小极大偏差稳健 M 估计AI 解读

Asymptotically min—max bias robust M-estimates of scale are obtained for positive random variables with ε-contaminated distributions, using any one of a broad class of loss functions of positive and negative bias. Any such estimate is a scaled order statistic, with the order statistic and scaling constant determined by ε, the nominal distribution, and the loss function. Some calculations for specific cases show that for a large range of ε the min—max order statistic solution…

实现对称性与同方差性的回归变换AI 解读

This article considers transformations in regression to eliminate skewness and heteroscedasticity of the response. We work with the transform-both-sides model where the relationship between the median response and the independent variables has been identified, at least tentatively. To preserve this relationship, the response and the regression model are transformed in the same way. Extending the work of others for the location parameter case, we propose an estimator that…

数量估计法中的受访者行为AI 解读

Some researchers argue that data obtained using magnitude estimation have metric properties superior to those of data obtained using traditional survey items. The analysis in this article examines evidence relevant to the assumptions that respondents can express ratios using numbers, can locate an internal continuum, and can use the standard stimulus effectively. The data are answers to 5 practice items designed to teach magnitude estimation using line lengths and up to 18…

基于回顾性发现机制的推断：输血相关艾滋病数据分析AI 解读

In some epidemiologic studies, identification of individuals for study is dependent on the occurrence of some event. Once an individual is identified, the time of a previous event, termed an initiating event, is determined retrospectively. This article considers problems of estimation when initiating events occur as a nonhomogeneous Poisson process, and the time s from the initiating event to the final event has pdf f(s) independent of the time of the initiating event. A…

带脉冲时间序列的非高斯模型AI 解读

A non-Gaussian autoregressive-like model is presented for time series that exhibit occasional large increases in value, termed pulses, and exponential decay between pulses. The model differs from a first-order autoregressive process in its incorporation of feedback between the distribution of the current innovation and the history of the process. Likelihood-based methods of inference for the model are developed, and an application to endocrinological data is given.

存在干扰参数时假设显著性检验的广义 p 值AI 解读

This article examines some problems of significance testing for one-sided hypotheses of the form H 0 : θ ≤ θ 0 versus H 1 : θ > θ 0, where θ is the parameter of interest. In the usual setting, let x be the observed data and let T(X) be a test statistic such that the family of distributions of T(X) is stochastically increasing in θ. Define Cx as {X : T(X) — T(x) ≥ 0}. The p value is p(x) = sup θ≤θ0 Pr(X ∈ Cx | θ). In the presence of a nuisance parameter η, there may not exist…

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实验随机化与正态理论推断的有效性AI 解读

This article examines how randomization helps to validate model-based probability statements. The asymptotic validity of normal-theory tests for means in multivariate linear models is established under general conditions. Numerical results are presented showing how randomization provides a limited degree of robustness in small experiments. The conditional relevance of randomization is also discussed. Consider the following additive model for a comparative experiment: Y = θ +…

非参数政策分析AI 解读

This article considers the problem of predicting the mean effect of a change in the distribution of certain policy-related variables on a dependent variable (Y). This is conventionally done using a parametric model. If, however, the conditional expectation of Y, given policy and nonpolicy variables X, is unaltered by the policy intervention, and if the support of X after the policy intervention lies within the support of X before the intervention, then this analysis can be…

扫描统计量分布的近似与界AI 解读

The scan statistic is used in many areas of science to test the null hypothesis of uniformity against a clustering alternative. This article derives approximations and bounds for the distribution of scan statistics. An extensive simulation study is carried out to compare the approximations and the bounds derived in this article with other known approximations and bounds. The new lower and upper bounds that have been derived are very useful in evaluating the approximations…

非球形协方差下重复测量方差分析的近似功效AI 解读

Violation of sphericity of covariance across repeated measures inflates Type I error rates in univariate repeated-measures analysis of variance. Hence the use of Geisser—Greenhouse or Huynh—Feldt is now common (to provide improved Type I error rate). With nonsphericity, no method has been available to compute power. A convenient method is suggested for approximating power and test size under nonsphericity. New approximations are suggested for (a) a weighted sum of…

随机序约束下的多元分布估计AI 解读

Let F and G be the cdf's of two p-dimensional multivariate distributions, such that F is stochastically larger than G. A straightforward derivation is given of the generalized maximum likelihood estimators of F and G, based on random samples from each population. An algorithmic approach to computing these estimators is described and motivating numerical examples are discussed. The special case when F and G correspond to multivariate ordinal contingency tables is also…

多元时间序列的自相关与随机性检验AI 解读

There exist several tests for autocorrelation and randomness in multiple time series. Unfortunately, the exact distributions of these statistics are unknown and the asymptotic distributions that are known do not provide adequate approximation to the exact ones in small samples. In this article, the test statistics are modified. Asymptotically, these modified statistics are equivalent to their original counterparts; however, it is found that the asymptotic distributions of…

多设计多元线性模型的秩推断AI 解读

Multivariate models more general than the standard multivariate linear model have received considerable attention in both the statistical and econometric literature; see Srivastava (1966, 1967, 1968) and Kleinbaum (1973). The multiple-design multivariate (MDM) linear model generalizes the standard multivariate linear model in the sense that a different design matrix is used for each response (dependent) variable. Important applications of the MDM linear model include…

由共享脆弱性诱导的二元生存模型AI 解读

When two observed survival times depend via a proportional-hazards model on the same unobserved variable, called a frailty, this common dependence induces an association between the observed times. This article considers the class of bivariate survival distributions that can arise in this way, extends it to allow negative association, and shows that the observable bivariate distribution determines the unobserved frailty distribution up to a scale parameter. A cross-ratio…

卡尔曼滤波模型的稳健化AI 解读

Kalman filter models based on the assumption of multivariate Gaussian distributions are known to be nonrobust. This means that when a large discrepancy arises between the prior distribution and the observed data, the posterior distribution becomes an unrealistic compromise between the two. In this article we discuss a rationale for how to robustify the Kalman filter. Specifically, we develop a model wherein the posterior distribution will revert to the prior when extreme…