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Biomedical subjects

Morris Meisner

Publications and source records attributed to Morris Meisner.

5 recordsLinked to original sources
PubMed2004

Estimating capacity requirements for mental health services after a disaster has occurred: a call for new data.

OBJECTIVES: We sought to estimate the extended mental health service capacity requirements of persons affected by the September 11, 2001, terrorist attacks. METHODS: We developed a formula to estimate the extended mental health service capacity requirements following disaster situations and assessed availability of the information required by the formula. RESULTS: Sparse data exist on current services and supports used by people with mental health problems outside of the formal mental health specialty sector. There also are few systematically collected data on mental health sequelae of disasters. CONCLUSIONS: We recommend research-based surveys to understand service usage in non-mental health settings and suggest that federal guidelines be established to promote uniform data collection of a core set of items in studies carried out after disasters.

Adult↗
PubMed2003

Estimating population size and duplication rates when records cannot be linked.

The capture-recapture approach to estimating the size of a population is a well-studied area of statistics. The number of distinct individuals, N(A) and N(B), on each of two lists, A and B, and the number common to both lists, N(AB), are used to form an estimate of the binomial probability of being on one of the lists, which then allows an estimate to be made of the size of the population. Critical to the method is an accurate count of N(AB). We consider situations in which this count is not available. Such problems arise in a variety of behavioural health contexts in which the need for protection of privacy may prevent sharing identifying information, so it is not possible to specifically match an individual who appears on one list with an individual on the other. Suppose that the birth dates and/or other demographics of individuals on each list are known. We introduce two methods for estimating the duplication rates and the size of the population. Conditioning on the set beta of birth dates of those on list B, N(A) and N(B), the maximum likelihood estimators (MLEs) and their variance are derived. The MLEs are based on the proportion of individuals on list A whose birth dates fall in beta. This approach is particularly useful if list B itself contains duplicates. The second model utilizes the full sample distribution of the birth dates. We generalize this approach to accommodate multiple demographic characteristics. The approaches are applied to the problem of estimating duplication rates and the population size of veterans who have mental illness in Kings County, NY. The data are lists of those receiving service from the Veterans Administration system and from providers funded or certified by the New York State Office of Mental Health.

Adolescent↗
PubMed2002

The familywise error rate of a simultaneous confidence band for the incremental net health benefit.

Interest in the use of net health benefit in cost-effectiveness analysis derives from its optimality property for decision-making. A description of the results of an economic evaluation of health care interventions is incomplete if it does not include point and interval estimates of this outcome measure. A simultaneous confidence band for the incremental net health benefit, INHB(lambda), for all lambda may be obtained by forming a confidence interval based on student's t statistic, and letting the willingness-to-pay value, lambda, run over all values. The familywise error rate (FWER) of the simultaneous confidence band is the probability that the confidence interval does not cover the true INHB(lambda) for some value of lambda. We show that the FWER equals P(T(2)>t(2)), where T(2) follows Hotelling's central distribution and that the simultaneous confidence band does not cover the true INHB(lambda) if and only if a T(2) based confidence ellipsoid does not cover the true mean c-e vector.

Cost-Benefit Analysis↗
PubMed2002

Statistical determination of cost-effectiveness frontier based on net health benefits.

Statistical methods are given for producing a cost-effectiveness frontier for an arbitrary number of programs. In the deterministic case, the net health benefit (NHB) decision rule is optimal; the rule funds the program with the largest positive NHB at each lambda, the amount a decision-maker is willing to pay for an additional unit of effectiveness. For bivariate normally distributed cost and effectiveness variables and a specified lambda, a statistical procedure is presented, based on the method of constrained multiple comparisons with the best (CMCB), for determining the program with the largest NHB. A one-tailed t test is used to determine if the NHB is positive. To obtain a statistical frontier in the lambda-NHB plane, we develop a method to produce the region in which each program has the largest NHB, by pivoting a CMCB confidence interval. A one-sided version of Fieller's theorem is used to determine the region where the NHB of each program is positive. At each lambda, the pointwise error rate is bounded by a prespecified alpha. Upper bounds on the familywise error rate, the probability of an error at any value of lambda, are given. The methods are applied to a hypothetical clinical trial of antipsychotic agents.

Algorithms↗