Estimating survival curves with left truncated and interval censored data via the ems algorithm

It is well-known that the nonparametric maximum likelihood estimator (NPMLE) of a survival function may severely underestimate the survival probabilities at very early times for left truncated data. This problem might be overcome by instead computing a smoothed nonparametric estimator (SNE) via the EMS algorithm. The close connection between the SNE and the maximum penalized likelihood estimator is also established. Extensive Monte Carlo simulations demonstrate the superior performance of the SNE over that of the NPMLE, in terms of either bias or variance, even for moderately large Samples. The methodology is illustrated with an application to the Massachusetts Health Care Panel Study dataset to estimate the probability of being functionally independent for non-poor male and female groups rcspectively.     

Stages of change among ethnically diverse college students

The authors applied the stage-of-change construct in the transtheoretical model to examine the distribution of Asian (n = 869), African American (n = 373), White (n = 1322), and Hispanic (n = 535) American undergraduate students across the 5 stages of change for exercise. Stage of change varied as a function of ethnicity. Higher percentages of minorities were in the precontemplation and contemplation stages. The likelihood of being in these stages was from 43% to 82% greater for minorities than for White students. Also examined were the congruency between stage of change and self-reported levels of physical activity. Half of the sedentary students and 15.6% of the active students were misclassified by the stage-of-change procedure. Misclassification rates were higher for minority women (27.8%) than for White women (17.8%) and for Asian students (24.6%) compared with all others (20.6%). The results of this study have implications for the design of physical activity interventions based on stage of change.     

The Importance of Ownership Arrangements in U.S. Agriculture1

Abstract According to a number of observers of the U.S. economy, large publicly traded corporations can be viewed as a social problem primarily because of their association with the concentration of wealth and power. In agriculture, nine states have laws which restrict or proscribe public corporations from engaging in farming. Also, groups and individuals have attempted to preserve non-corporate production enterprises in agriculture through the establishment of direct markets such as farmers' markets. Proponents of such efforts believe public corporations have negative economic impacts; opponents of such efforts, especially efforts to establish and retain anti-corporate farming laws, argue that corporations can provide economic benefits to rural areas. These debates beg the question of whether ownership and direct marketing arrangements have important influences on economic outcomes such as levels of cash returns from farming and increases in the number of farms realizing cash gains. Using multi-year, county-level data from the Census of Agriculture, this study finds that, even when holding a number of important variables constant, ownership arrangements, as well as the (interaction between the percentage of total sales which are direct sales and the percentage of farms selling directly, are important determinants of both net cash returns and the percentage of farms realizing cash gains.     

INVERSE GAUSSIAN CONTROL CHARTS

Control charts typically used to monitor process centrality and dispersion either assume normally distributed output or appeal to the viability of the central limit theorem. This appeal to the central limit theorem is frequently made on behalf of samples consisting of 10 or fewer items. Control charts for centrality and dispersion are presented for processes with inverse Gaussian distributed output.