Mental health and behavioral problems of youth in the child welfare system: residential treatment centers compared to therapeutic foster care in the Odyssey Project population

This is the first multisite, prospective study of behavioral and mental health disorders of youth in residential treatment centers (RTC) and therapeutic foster care (TFC), and the first study to compare the two. This study addressed two questions in a sample of 22 agencies in 13 states: (1) how prevalent were emotional and behavioral disorders in the youth admitted to RTCs and TFC?, and (2) were the youth in RTCs significantly more likely to be disturbed than youth served in TFCs? Data were drawn from the Time 1 phase of the longitudinal national "Odyssey Project" developed by the Child Welfare League of America (1995). Measures included an extensive child and family characteristics form (CFC) and the Child Behavior Checklist (CBCL). The results revealed extremely high levels of behavioral and mental health disorders in the sample as a whole, well above the norms for a non-child welfare population. The prevalence of disorder in the RTC population was substantially greater than in the TFC population.     

Grandparents Responsible for Grandchildren in Native‐American Families*

Objectives. The primary goal of this article is to examine factors associated with grandparent care giving within the American Indian/Alaska Native (AIAN) population. Methods. Data from the 2000 Census of Population, 5% Public Use Microdata Sample, are used to evaluate a multivariate logistic regression model focusing on living with and caring for grandchildren. Particular emphasis is placed on characteristics that may reflect culturally‐based ideas about grandparents' responsibility for the care of their grandchildren. Results. Indicators related to Native‐American identity—specifically, reporting race as AIAN only rather than mixed race, reporting tribal membership, and living in a nonmetropolitan area of an “Indian” state—increase the likelihood of being responsible for a grandchild among Native‐American singles and couples aged 45 and over. Conclusions. Cultural and resource characteristics combine to produce high levels of grandparent care giving within the AIAN population. Inasmuch as those with lower educational and economic resources are especially likely to have responsibility for a grandchild, special attention should be directed toward ensuring adequate support for these caregivers.     

Deterministic Evolution of Strength in Multiple Comparisons Models: Who is the Greatest Golfer?

We present a statistical methodology for fitting time‐varying rankings, by estimating the strength parameters of the Plackett–Luce multiple comparisons model at regularly spaced times for each ranked item. We use the little‐known method of barycentric rational interpolation to interpolate between the strength parameters so that a competitor's strength can be evaluated at any time. We chose the time‐varying strengths to evolve deterministically rather than stochastically, a preference that we reason often has merit. There are many statistical and computational problems to overcome on fitting anything beyond ‘toy’ data sets. The methodological innovations here include a method for maximizing a likelihood function for many parameters, approximations for modelling tied data and an approach to the elimination of secular drift of the estimated ‘strengths’. The methodology has obvious applications to fields such as marketing, although we demonstrate our approach by analysing a large data set of golf tournament results, in search of an answer to the question ‘who is the greatest golfer of all time?’     

Control variates for stochastic gradient MCMC

Statistics and Computing - It is well known that Markov chain Monte Carlo (MCMC) methods scale poorly with dataset size. A popular class of methods for solving this issue is stochastic gradient...     

Service Package Switching in Hotel Revenue Management Systems

Revenue Management Systems (RMS) are commonly used in the hotel industry to maximize revenues in the short term. The forecasting‐allocation module is a key tactical component of a hotel RMS. Forecasting involves estimating demand for service packages across all stayover nights in a planning horizon. A service package is a unique combination of physical room, amenities, room price, and advance purchase restrictions. Allocation involves parsing the room inventory among these service packages to maximize revenues. Previous research and existing revenue management systems assume the demand for a service package to be independent of which service packages are available for sale. We develop a new forecasting‐allocation approach that explicitly accounts for this dependence. We compare the performance of the new approach against a baseline approach using a realistic hotel RMS simulation. The baseline approach reflects previous research and existing industry practice. The new approach produces an average revenue increase of at least 16% across scenarios that reflect existing industry conditions.     

A Comparative Revenue Analysis of Hotel Yield Management Heuristics

Yield management is the dynamic pricing, overbooking, and allocation of perishable assets across market segments in an effort to maximize short-term revenues for the firm. Numerous optimization heuristics for allocation and overbooking exist for the airline industry, whose perishable asset is the airplane seat. When an airplane departs, no revenue is gained from the empty seat(s). In the hotel industry, the perishable asset is the hotel room-once a room is left empty for a night, that night's revenue cannot be recaptured. The literature on yield management heuristics for the hotel industry is sparse. For the hotel operating environment, no research has adequately (1) integrated overbooking with allocation, (2) modeled the phenomenon of hotel patrons extending or contracting their stay at a moment's notice, or (3) performed a realistic performance comparison of alternative heuristics. This research develops (1) two hotel-specific algorithms that both integrate overbooking with the allocation decisions, (2) a simulation model to reproduce realistic hotel operating environments, and (3) compares the performance of five heuristics under 36 realistic hotel operating environments. Seven conclusions are reached with regard to which heuristic(s) perform best in specific operating environments. Generally, heuristic selection is very much dependent on the hotel operating environment. A counterintuitive result is that in many operating environments, the simpler heuristics work as well as the more complex ones.     

Multiple Attribute Decision Making with Inexact Value-Function Assessment

A major issue in value-function assessment is the possibility of receiving an indefinite response from a decision maker to a question about preferences. The conventional treatment requires a single, definite response from the decision maker. This approach either assumes that response error is zero or accepts the final solution as only approximate, without knowing how approximate it might be. In this paper we examine the issue of indefinite responses, define it more precisely, and present a method for incorporating it into decision making. The method is adaptive in that it is iterative and interactive with the decision maker who, at each iteration, is provided with information regarding the potential advantage of answering more trade-off questions and/or answering questions more carefully to reduce response error. In contrast to other approaches that “force” rationality and decisiveness, we work with irrationality and indecisiveness on the part of the decision maker. The method is demonstrated for the case of concave, increasing value functions.