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Transformations of the explanatory variables in the logistic regression model for binary data

二元数据 Logistic 回归中的解释变量变换

Some results are presented on improving the fit of the logistic regression model for binary data by transforming the vector of explanatory variables. The methods are based on consideration of the distributions of these variables conditional on outcome group. The transformations required are the functions of the explanatory variables which appear in the log density ratio of the conditional distributions.

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Crossover designs for comparing treatments with a control

用于比较多种处理与对照的交叉设计

We introduce a class of crossover designs with residual effects for experimental situations in which primary interest centres on the comparison of several test treatments to a control treatment rather than on all pairwise comparisons among the treatments. We shall call these designs ‘control balanced residual effects designs’. Their structure is studied in detail, some methods of their construction are given and their relative efficiencies are evaluated.

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A modified log rank test for highly stratified data

适用于高度分层数据的修正对数秩检验

Clinical trials often employ a stratified randomization so that treatment arms are balanced within prognostic factors. In these circumstances the use of the ordinary log rank test for comparing treatment groups with respect to survival is invalid. The stratified log rank test, although valid, loses efficiency as the number of strata increases. This paper proposes a modified log rank test that is fully efficient when there is no strata effect and is more efficient than the…

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Logistic regression analysis of sample survey data

抽样调查数据的逻辑回归分析

Standard chi-squared, X2 or likelihood ratio, G2, test statistics for logistic regression analysis, involving a binary response variable, are adjusted to take account of the survey design. These adjustments are based on certain generalized design effects. Logistic regression diagnostics to detect any outlying cell proportions in the table and influential points in the factor space are also developed, taking account of the survey design. Finally, the results are used to…

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Sensitivity analysis for certain permutation inferences in matched observational studies

匹配观察性研究中部分置换推断的敏感性分析

In observational studies, treatments are not randomly assigned to experimental units, so that randomization tests and their associated interval estimates are not generally applicable. In an effort to compensate for the lack of randomization, treated and control units are often matched on the basis of observed covariates; however, the possibility remains of bias due to residual imbalances in unobserved covariates. A general though simple method is proposed for displaying the…

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Outliers and Residual Distributions in Logistic Regression

Logistic 回归中的异常值与残差分布

Detection of outliers and other diagnostics based on residuals have gained widespread use in linear regression. Logistic regression has been both blessed and hindered by this development. Certainly logistic regression requires procedures to detect global and local model weaknesses. Thus the wealth of work done in linear regression provides guides and suggestions that may, with care and ingenuity, be applied to logistic regression. Several innovative attempts in this…

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The Gini Coefficient and Poverty Indexes: Some Reconciliations

基尼系数与贫困指数:若干协调关系

Poverty is usually defined as the extent to which individuals in a society or community fall below a minimal acceptable standard of living. An index of poverty is generally based on the proportion (α) of the poor people and their income distribution through the income gap ratio (β) (i.e., the average income gap of the poor people from the poverty line ω, taken as a ratio to ω itself) and other measures of income inequalities. In this context, the well-known Gini coefficient…

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Statistics and Causal Inference

统计学与因果推断

Problems involving causal inference have dogged at the heels of statistics since its earliest days. Correlation does not imply causation, and yet causal conclusions drawn from a carefully designed experiment are often valid. What can a statistical model say about causation? This question is addressed by using a particular model for causal inference (Holland and Rubin 1983; Rubin 1974) to critique the discussions of other writers on causation and causal inference. These…

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A Successive Differences Method for Growth Curves with Missing Data and Random Observation Times

缺失数据与随机观测时点下增长曲线的相邻差分法

Incomplete growth curve data can be analyzed by the successive differences (SD) method, which uses the difference in consecutive pairs of observations for all subjects having two or more repeated measures. We have generalized it to handle varying observation times as well by partitioning the time interval spanned by all repeated measures into subintervals. The model is developed, including test statistics for the hypotheses of parallelism and of no change in response level…

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The Gini Coefficient and Poverty Indexes: Some Reconciliations

基尼系数与贫困指数之间的协调关系

Poverty is usually defined as the extent to which individuals in a society or community fall below a minimal acceptable standard of living. An index of poverty is generally based on the proportion (α) of the poor people and their income distribution through the income gap ratio (β) (i.e., the average income gap of the poor people from the poverty line ω, taken as a ratio to ω itself) and other measures of income inequalities. In this context, the well-known Gini coefficient…

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Censored Observations, Repeated Measures and Mixed Effects Models: An Approach Using the EM Algorithm and Normal Errors

删失观测、重复测量与混合效应模型:正态误差下的 EM 方法

Maximum likelihood estimation of a vector regression parameter and variance com ponents is considered for the mixed effects model when observations are right censored. A general scheme of estimation is given using the EM algorithm and detailed results found for the model with between and within block variation. This model is applied to the logarithms of survival times from a repeated measures design.

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Estimating Distribution Functions from Survey Data

利用调查数据估计分布函数

A simple method for estimating population distribution functions and associated quantiles from sample survey data is described and some asymptotic theory for it presented. The method assumes a model-based approach to survey estimation and allows auxiliary population information to be directly incorporated into the estimation process. Monte Carlo results comparing the proposed method with conventional design-based methods are given. These suggest that the model-based approach…

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Pooling Under Misspecification: Some Monte Carlo Evidence on the Kmenta and the Error Components Techniques

误设下的合并估计:Kmenta 与误差分量方法的蒙特卡洛证据

Two different methods for pooling time series of cross section data are used by economists. The first method, described by Kmenta, is based on the idea that pooled time series of cross sections are plagued with both heteroskedasticity and serial correlation.The second method, made popular by Balestra and Nerlove, is based on the error components procedure where the disturbance term is decomposed into a cross-section effect, a time-period effect, and a remainder.Although…

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Confidence Intervals for Elasticity Estimators in Translog Models

超越对数模型中弹性估计量的置信区间

This paper examines the distribution fu nctions of elasticity estimators in translog demand models. The authors consider the normaland ratio-of-normals distributions and present confidence intervals for the elasticity estimators. The results suggest that only elasticity estimato rs based on the means of the actual cost shares are likely to follow either the normal or ratio-of-normals distribution function. Examination of three published empirical studies demonstrates that…

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Statistical Properties of Generalized Method-of-Moments Estimators of Structural Parameters Obtained From Financial Market Data

利用金融市场数据估计结构参数的广义矩估计量的统计性质

The article examines the properties of generalized method of moments GMM estimators of utility function parameters. The research strategy is to apply the GMM procedure to generated data on asset returns from stochastic exchange economies; discrete methods and Markov chain models are used to approximate the solutions to the integral equations for the asset prices. The findings are as follows: (a) There is variance/bias trade-off regarding the number of lags used to form…

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Confidence Bands for Percentiles in the Linear Regression Model

线性回归模型中百分位数的置信带

Simultaneous confidence intervals for percentiles of the normal regression model similar to those given by Steinhorst and Bowden (1971) are considered. Kanofsky's (1968) confidence band for a single normal distribution is modified and extended to the regression model. The confidence bands that are simultaneous in all percentiles provide corresponding confidence bands for the cumulative conditional normal distribution functions. The various procedures are compared with…

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Confidence Bands for Percentiles in the Linear Regression Model

线性回归模型中百分位数的置信带

Simultaneous confidence intervals for percentiles of the normal regression model similar to those given by Steinhorst and Bowden (1971) are considered. Kanofsky's (1968) confidence band for a single normal distribution is modified and extended to the regression model. The confidence bands that are simultaneous in all percentiles provide corresponding confidence bands for the cumulative conditional normal distribution functions. The various procedures are compared with…

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Quantile Processes with Statistical Applications.

分位数过程及其统计应用

A Preliminary Study of Quantile Processes A Weak Convergence of the Normed Sample Quantile Process Strong Approximations of the Normed Quantile Process Two Approaches to Constructing Simultaneous Confidence Bounds for Quantiles Weak Convergence of Quantile Processes in Weighted Sup-Norm Metrics and Further Strong Approximations On Bahadur's Representation of Sample Quantiles and on Kiefer's Theory of Deviations Between the Sample Quantile and Empirical Processes Quadratic…

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