Strategic planning in smaller rapid growth companies

The research reported in this article is based on a study of the strategic planning practices of the 500 fastest growing privately held smaller companies in the United States ranked according to percentage of sales increases from 1978 to 1982.^p1 Based on the information provided, a clear picture emerges regarding the actual role of strategic planning in rapid growth companies.     

Empirical Non-Parametric Control Charts: Estimation Effects and Corrections

Owing to the extreme quantiles involved, standard control charts are very sensitive to the effects of parameter estimation and non-normality. More general parametric charts have been devised to deal with the latter complication and corrections have been derived to compensate for the estimation step, both under normal and parametric models. The resulting procedures offer a satisfactory solution over a broad range of underlying distributions. However, situations do occur where even such a large model is inadequate and nothing remains but to consider non- parametric charts. In principle, these form ideal solutions, but the problem is that huge sample sizes are required for the estimation step. Otherwise the resulting stochastic error is so large that the chart is very unstable, a disadvantage that seems to outweigh the advantage of avoiding the model error from the parametric case. Here we analyse under what conditions non-parametric charts actually become feasible alternatives for their parametric counterparts. In particular, corrected versions are suggested for which a possible change point is reached at sample sizes that are markedly less huge (but still larger than the customary range). These corrections serve to control the behaviour during in-control (markedly wrong outcomes of the estimates only occur sufficiently rarely). The price for this protection will clearly be some loss of detection power during out-of-control. A change point comes in view as soon as this loss can be made sufficiently small.     

Dementia Problem Behavior and the Production of Informal Caregiving Services

Informal caregivers of individuals with Alzheimer's disease spend a considerable amount of time providing care. In this paper, we use Grossman's health production and Becker's time allocation models to develop a model of informal care provision to elderly dementia patients. In our model, time inputs produce caregiving services, which provides utility to the caregiver, but reduces leisure. We assume that time is less productive of services on the margin as the disease progresses. In this framework, an increase in patients' disease severity does not necessarily increase informal caregiver time input. The cost of formal care establishes a reservation price for informal caregiving. When the costs of informal caregiving rise above this reservation level, the patient is institutionalized. We test empirically the effect of deterioration in the patients' condition, proxied by both disease severity and dementia problem behavior, on informal caregiving time. We find that dementia-related problem behaviors and functional limitations significantly increase inputs of informal caregiving time. Patients' problem behavior exerts a modifying effect on functional limitations, and patients' comorbidities have no effect on informal caregiving time.     

Facilitative Aspects of Field Research with Deviant Street Populations*

The authors examine facilitative aspects of field research with deviant street populations. Based on the authors' research with the homeless and with male street prostitutes, the facilitative aspects include access to settings, social relationships, acquisition of information, and the maintenance of researcher interest. The authors argue that in each of these aspects street deviants may in some ways be easier to study than other populations. The paper concludes with suggestions for maximizing the efficiency and quality of fieldwork with specific deviant populations.     

Campus attitudes toward alcohol and drugs in a deep southern university.

In our zeal to deal with alcohol and drug abuse, we may have a distorted picture of what the majority of college students actually think about alcohol and drug use. Students in this study done at a public university located in the Deep South report being generally intolerant of substance abuse.     

An introduction to econometric applications of empirical process theory for dependent random variables

This paper discusses some uses in econometrics of empirical process theory for dependent rendom variables. Examples considered include non-standard parametric hypotheses tests and semiparametric estimation. The application of bracketing functional limit results is discussed in some detail     

A modified random-effect procedure for combining risk difference in sets of 2×2 tables from clinical trials

Summary Meta-analyses of sets of clinical trials often combine risk differences from several 2×2 tables according to a random-effects model. The DerSimonian-Laird random-effects procedure, widely used for estimating the populaton mean risk difference, weights the risk difference from each primary study inversely proportional to an estimate of its variance (the sum of the between-study variance and the conditional within-study variance). Because those weights are not independent of the risk differences, however, the procedure sometimes exhibits bias and unnatural behavior. The present paper proposes a modified weighting scheme that uses the unconditional within-study variance to avoid this source of bias. The modified procedure has variance closer to that available from weighting by ideal weights when such weights are known. We studied the modified procedure in extensive simulation experiments using situations whose parameters resemble those of actual studies in medical research. For comparison we also included two unbiased procedures, the unweighted mean and a sample-size-weighted mean; their relative variability depends on the extent of heterogeneity among the primary studies. An example illustrates the application of the procedures to actual data and the differences among the results. This research was supported by Grant HS 05936 from the Agency for Health Care Policy and Research to Harvard University.