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At least 55 records · Page 3Linked to original sources
PubMed1991

Computer graphics representation of a statistical model used with computer-aided diagnosis.

A description of computer graphics of a multidimensional model that is used with computer-aided diagnosis or prognosis is presented. The model is discussed and computer graphics of the model are developed. The computer graphics are suitable as visual supplements for presenting the computer-aided diagnostic model to individuals who may be inexperienced in multivariate statistics.

Animals↗
PubMed1979

Statistical models of the demand for emergency medical services in an urban area.

First- and second-order statistical regression models are presented for the Emergency Medical Services (EMS) demand in an urban area as it relates to various socioeconomic, demographic, and other characteristics of the area. Individual models are formulated for different types of medical emergencies with the city of Atlanta, GA, serving as the data base. These models are generally shown to provide excellent fits to the empirical data.

Emergency Medical Services↗
PubMed1990

Statistical modelling of the AIDS epidemic for forecasting health care needs.

The objective of this paper is to develop statistical methods for estimating current and future numbers of individuals in different stages of the natural history of the human immunodeficiency (AIDS) virus infection and to evaluate the impact of therapeutic advances on these numbers. The approach is to extend the method of back-calculation to allow for a multistage model of natural history and to permit the hazard functions of progression from one stage to the next to depend on calendar time. Quasi-likelihood estimates of key quantities for evaluating health care needs can be obtained through iteratively reweighted least squares under weakly parametric models for the infection rate. An approach is proposed for incorporating into the analysis independent estimates of human immunodeficiency virus (HIV) prevalence obtained from epidemiologic surveys. The methods are applied to the AIDS epidemic in the United States. Short-term projections are given of both AIDS incidence and the numbers of HIV-infected AIDS-free individuals with CD4 cell depletion. The impact of therapeutic advances on these numbers is evaluated using a change-point hazard model. A number of important sources of uncertainty must be considered when interpreting the results, including uncertainties in the specified hazard functions of disease progression, in the parametric model for the infection rate, in the AIDS incidence data, in the efficacy of treatment, and in the proportions of HIV-infected individuals receiving treatment.

Acquired Immunodeficiency Syndrome↗
PubMed1991

A statistical model for in-vitro assessment of patient sensitivity to cytotoxic drugs.

Formation of colonies in semisolid medium is an assay used for the study of stem cell characteristics in hematopoietic and solid tumors. Previous experience with leukemia patients failed to show an association between the reduction in colony formation observed when patient blast cells were exposed to increased concentrations of an anticancer agent, and the subsequent patient response to the agent. By introducing a model that takes into account the possibility of a resistant subpopulation of clonogenic cells, the paper demonstrates that the null result was due to an inadequate summarization of the dose-response curve, and in fact a statistically and biologically significant association exists between one of the parameters of the model and patient response. The properties, implementation, and interpretation of the model are discussed.

Biometry↗
PubMed1975

Life games and statistical models.

A set of equations is obtained, which describes the rules of a class of games (life games). These games simulate the processes of growth, death, survival, and competition. The equations are nonlinear difference equations, where the degree of nonlinearity is directly related to the number of interacting neighbors. The time evolution and the development of geometric patterns can be studied starting from these equations. Extensions and generalizations, such as the introduction of stochastic elements, can easily be accommodated in the formalism. Some significant unsolved problems are noted.

Biological Evolution↗
PubMed1991

Statistical model in tests for eye irritants.

A test used to classify substances for eye irritancy, as required by the Consumer Product Safety Commission, is performed on 1-3 groups of 6 albino rabbits in a sequential manner. When the statistical implications of the test are realized, it is possible for a substance to be classified as an irritant with fewer reactions than the number required for it to be classified as not an irritant. A procedure is given for correcting the inconsistency in the current test, and an alternative test, which considerably reduces the number of animals required, is proposed. Probability models and expected sample size calculations have been derived.

Animal Testing Alternatives↗
PubMed1976

Some theory of reference values. II. Comparison of some statistical models of intraindividual variation in blood constituents.

Three models of intraindividual variation are reviewed, and statistical methods for distinguishing among them are discussed. Application of these methods to short series of observations from healthy individuals indicates that, in the large majority of cases, a strictly homeostatic model is appropriate for such constituents as serum calcium and magnesium. In less closely controlled variables, e.g., serum cholesterol and uric acid, a nonstationary, "rndom walk" model appears moresuitable in most cases. A more general autoregressive model, which includes the other models as extreme cases, could be used to describe all degrees of homeostatic control. This model is more complex, however, and requires at least 10 observations to yield estimates of acceptable precision. Moreover, it is sensitive to fluctuations in within-batch analytical variance. When biological variance is small relative to analytical variance, all three models yield essentially the same predicated values. To illustrate their use, these models have been applied to four short individual series of cholesterol observations showing increasing amounts of intrapersonal variation over long periods of time. I suggest that when less than 10 observations over time are available, the strictly homeostatic model and the nonstationary model be used to derive a "critical range" for assessing future changes. When longer series are available, the more general model might replace the other two for this purpose, if analytical variation has remained reasonably stable (within +/- 20% of its average value) during the period of observation. Much more experience with the use of all three models in health monitoring programs would be highly desirable.

Analysis of Variance↗
PubMed1992

A statistical model and computer program to estimate association constants for the binding of fluorescent-labelled monoclonal antibodies to cell surface antigens and to interpret shifts in flow cytometry data resulting from alterations in gene expression.

Flow cytometry is used to obtain estimates for the distribution of fluorescent ligands bound to cell surface receptors throughout a cell sample. The equipment used provides light scattering parameters and also cell staining data in the form of dot plots and histograms of fluorescence intensities and the frequency of occurrence of particular fluorescence intensities. It is then assumed that fluorescence intensity is proportional to the number of labelled ligands bound to surface receptors. In this paper we present an outline of a statistical theory to account for the stretching and translation of such flow cytometry profiles which occur either as a result of alterations in gene expression, or from changing the sub-saturating concentration of fluorescent-labelled monoclonal antibodies or lectins used to stain the cells. We describe how the theory has been incorporated into two programs CSAFIT (cell surface antigen fit) and MAKCSA (make data to test CSAFIT). The program CSAFIT can be used to estimate two parameters, alpha and beta, by constrained non-linear regression analysis of the flow cytometry profiles. If the shift results from changes in the concentration of a staining agent then the estimates alpha and beta calculated by CSAFIT are functions of the ligand concentration, the ligand type and the cell line characteristics. They quantify the stretch and translation events that are encountered in flow cytometry. So when the parameter estimates alpha and beta are then further analysed as functions of ligand concentration, estimates for the average association constant K for the binding-site/ligand interaction can be obtained. This paper describes details of the development of programs CSAFIT and MAKCSA. We also discuss the distribution of parameter estimates calculated by CSAFIT and the overall performance of CSAFIT as assessed by simulation studies using data generated by MAKCSA.

Antibodies, Monoclonal↗
PubMed1990

Statistical modeling of the effects of drug combinations.

A method is described for identifying and quantitating departures from additivity (i.e., synergism and antagonism) when drugs having like effects are given in combination. It is applicable for both graded and quantal (e.g., after probit or logit transformation) responses. Log(dose)-response curves of both drugs should be linear but need not be parallel. The following model is fitted to dose-response data for both the individual drugs and combinations of drugs: Y = beta 0 + beta 1 log(A + P.B + beta 4(A.P.B)1/2) where Y is the response, A is the amount of drug A, B is the amount of drug B, and P is a relative potency of the drugs given by log(P) = beta 2 + beta 3 log(B'), in which B' is the solution to B' - B - A/P = 0. If log(dose)-response curves of the two drugs are parallel, beta 3 = 0, and P becomes a constant parameter to be estimated. A positive value of beta 4 corresponds to synergism and a negative value to antagonism. Hypothesis tests may be carried out to determine whether beta 4 is significantly different from zero.

Dose-Response Relationship, Drug↗
PubMed1990

A note on the use of statistical models in epidemiologic research on illicit drug use.

This essay aims to stimulate thinking or to remind readers about the shortcomings of standardized regression coefficients and related statistical measures in epidemiologic research on illicit drug use. This is accomplished primarily with a set of examples based on simulated epidemiologic data in which the standardized regression coefficient is shown to co-vary dramatically with frequency of the outcome variable. The basic thrust of this critique of commonly used regression models is not new; it has appeared elsewhere several times. Nevertheless, in epidemiologic research on illicit drug use, there is a continuing use of standardized regression coefficients and other margin-sensitive statistical measures without comment on their shortcomings. Thus, a specific critique with illustrations might have value.

Adolescent↗
PubMed1992

[Statistic modeling of geographic and epidemiologic variations].

In epidemiology, studies of the geographical variations of mortality or incidence rates for some chronic diseases have often given rise to etiological clues concerning those diseases. In this framework the variables concerned have a spatially autocorrelated structure which has to be taken into account in the statistical analysis. The statistical techniques used to study in the first place the spatial variations of mortality rates and then the joint geographical variations of mortality and exposure indices are reviewed. Emphasis is placed on the importance played by the geographical scale of the analysed data in the modelling process as well as on the interpretation problems of geographical correlation studies.

Bias↗
PubMed1992

Multi-level statistical models in studies of periodontal diseases.

Periodontal data typically have a hierarchical structure, with sites grouped within individuals, and individuals grouped within communities. Also, the occasion may be regarded as another level since the acquired knowledge indicates that periodontal disease activity may vary over time. Conventional statistical tests are based on unilevel analysis of data. However, this approach to statistical analysis is often inconvenient in periodontal research because of the variation in the outcome variables between the various levels in the hierarchy. Lately there have been important developments in the statistical theory which have made available powerful statistical techniques for analyzing multilevel or hierarchical data. This report describes a new approach for analyzing periodontal data and uses an illustrative example to build a model which explains part of the variability in the response variable. The results from this analysis are then compared to results from an earlier report which uses unilevel methods and the findings discussed. The present multilevel approach has several advantages over unilevel methods, mainly due to its statistical validity and efficiency. Further, it permits the incorporation of explanatory variables measured at the site and the subject levels, and those which vary across the time points. Multilevel analyses have a promising potential and are expected to have a significant impact on periodontal research.

Age Factors↗