Asymptotic bias in the linear mixed effects model under non-ignorable missing data mechanisms

Summary.  In longitudinal studies, missingness of data is often an unavoidable problem. Estimators from the linear mixed effects model assume that missing data are missing at random. However, estimators are biased when this assumption is not met. In the paper, theoretical results for the asymptotic bias are established under non-ignorable drop-out, drop-in and other missing data patterns. The asymptotic bias is large when the drop-out subjects have only one or no observation, especially for slope-related parameters of the linear mixed effects model. In the drop-in case, intercept-related parameter estimators show substantial asymptotic bias when subjects enter late in the study. Eight other missing data patterns are considered and these produce asymptotic biases of a variety of magnitudes.     

解决我国农业剩余劳动力就业问题的思路

农业剩余劳动力的就业问题 ,是我国经济中的一个重要问题。要解决好这一问题 ,就需要制定引导农业劳动力转移的战略 ,多方寻求劳动力转移的途径 ,努力提高农业劳动力素质 ,建立健全劳动力市场 ,营造有利于农业剩余劳动力就业的制度环境 ,控制人口过快增长     

林业发展阶段研究概述

阶段性是事物发展必须遵循的一个客观规律,林业的发展同样也具有阶段性.只有充分认识各个时期林业发展所处的历史阶段和相应特征,才能更好地制定政策和发展战略.该文将以往的林业方面的阶段性研究加以综述,以期获得收益和启发,并为以后的研究打下基础.     

MEANINGFUL REGRESSION AND ASSOCIATION MODELS FOR CLUSTERED ORDINAL DATA

Many proposed methods for analyzing clustered ordinal data focus on the regression model and consider the association structure within a cluster as a nuisance. However, the association structure is often of equal interest—for example, temporal association in longitudinal studies and association between responses to similar questions in a survey. We discuss the use, appropriateness, and interpretability of various latent variable and Markov models for the association structure and propose a new structure that exploits the ordinality of the response. The models are illustrated with a study concerning opinions regarding government spending and an analysis of stability and change in teenage marijuana use over time, where we reveal different behavioral patterns for boys and girls through a comprehensive investigation of individual response profiles.     

Rainfall interception by Santa Monica's municipal urban forest

Effects of urban forests on rainfall interception and runoff reduction have been conceptualized, but not well quantified. In this study rainfall interception by street and park trees in Santa Monica, California is simulated. A mass and energy balance rainfall interception model is used to simulate rainfall interception processes (e.g., gross precipitation, free throughfall, canopy drip, stemflow, and evaporation). Annual rainfall interception by the 29,299 street and park trees was 193,168 m³ (6.6 m³/tree), or 1.6% of total precipitation. The annual value of avoided stormwater treatment and flood control costs associated with reduced runoff was $110,890 ($3.60/tree). Interception rate varied with tree species and sizes. Rainfall interception ranged from 15.3% (0.8 m³/tree) for a small Jacaranda mimosifolia (3.5 cm diameter at breast height) to 66.5% (20.8 m³/tree) for a mature Tristania conferta (38.1 cm). In a 25-year storm, interception by all street and park trees was 12,139.5 m³ (0.4%), each tree yielding $0.60 (0.4 m³/tree) in avoided flood control costs. Rainfall interception varied seasonally, averaging 14.8% during a 21.7 mm winter storm and 79.5% during a 20.3 mm summer storm for a large, deciduous Platanus acerifolia tree. Effects of differences in temporal precipitation patterns, tree population traits, and pruning practices on interception in Santa Monica, Modesto, and Sacramento, California are described.