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At least 469 records · Page 26Linked to original sources
PubMed1993

Clinical trials with velnacrine: (PROPP) the physician reference of predicted probabilities--a statistical model for the estimation of hepatotoxicity risk with velnacrine maleate.

Safety observations during the clinical development of Mentane (velnacrine maleate) have included the occurrence of generally asymptomatic liver enzyme elevations confined to patients with Alzheimer's disease (AD). The clinical presentation of this reversible hepatocellular injury is analogous to that reported for tetrahydroaminoacridine (THA). Direct liver injury, possibly associated with the production of a toxic metabolite, would be consistent with reports of aberrant xenobiotic metabolism in Alzheimer's disease patients. Since a patient related aberration in drug metabolism was suspected, a biostatistical strategy was developed with the objective of predicting hepatotoxicity in individual patients prior to exposure to velnacrine maleate. The method used logistic regression techniques with variable selection restricted to those items which could be routinely and inexpensively accessed at screen evaluation for potential candidates for treatment. The model was to be predictive (a marker for eventual hepatotoxicity) rather than a causative model, and techniques employed "goodness of fit", percentage correct, and positive and negative predictive values. On the basis of demographic and baseline laboratory data from 942 patients, the PROPP statistic was developed (the Physician Reference Of Predicted Probabilities). Main effect variables included age, gender, and nine hematological and serum chemistry variables. The sensitivity of the current model is approximately 49%, specificity approximately 88%. Using prior probability estimates, however, in which the patient's likelihood of liver toxicity is presumed to be at least 30%, the positive predictive value ranged between 64-77%. Although the clinical utility of this statistic will require refinements and additional prospective confirmation, its potential existence speaks to the possibility of markers for idiosyncratic drug metabolism in patients with Alzheimer's disease.

Age Factors↗
PubMed1999

An equilibrium statistical model for the spreading phase of open-ocean convection.

A "most probable state" equilibrium statistical theory for random distributions of hetons in a closed basin is developed here in the context of two-layer quasigeostrophic models for the spreading phase of open-ocean convection. The theory depends only on bulk conserved quantities such as energy, circulation, and the range of values of potential vorticity in each layer. The simplest theory is formulated for a uniform cooling event over the entire basin that triggers a homogeneous random distribution of convective towers. For a small Rossby deformation radius typical for open-ocean convection sites, the most probable states that arise from this theory strongly resemble the saturated baroclinic states of the spreading phase of convection, with a stabilizing barotropic rim current and localized temperature anomaly.

Journal Article↗
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↗
PubMed1997

On the statistical modelling of coronary arteriographic data: dynamics of coronary atherosclerosis related to systemic and focal parameters. REGRESS Study Group. Regression Growth Evaluation Statin Study.

Existing methods to analyse data from repeated arteriographic progression/regression studies are restrictive and do not fully explore the dynamics of coronary artherosclerosis. We present a new approach making a distinction between new occlusions, new lesions, and growth of existing lesions. Random effect models, based on the logistic, the Poisson, and the normal distribution are proposed with correlation depending on distance. The data from the Regression Growth Evaluation Statin Study (REGRESS) are used to validate the model. Lipid lowering treatment of pravastatin resulted in less growth of existing lesions and fewer new lesions than when placebo was given. Fewer new lesions were found in segments influenced by percutaneous transluminal coronary angioplasty (PTCA) than in segments not influenced by PTCA. Similarly, the growth of lesions influenced by PTCA was smaller than lesions not influenced by PTCA. More new occlusions were found in segments influenced by coronary arterial bypass grafting (CABG) than in segments not influenced by CABG, but 98 per cent of the new occlusions were located proximal to the bypass anastomosis. Similarly, existing lesions proximal to the bypass anastomosis showed larger growth (p < 0.001). We conclude that our new approach for analysing the arteriographic data from repeated coronary arteriographic studies appeared a fruitful way to analyse the dynamics of coronary atherosclerosis.

Angioplasty, Balloon, Coronary↗
PubMed1983

Twin concordance for a binary trait. I. Statistical models illustrated with data on drinking status.

A flexible method based on maximum likelihood theory is introduced for the analysis of binary response data in twins. The method allows for explanatory variables such as age and sex, is free of the untestable distributional assumption of bivariate normality of liability, and makes more efficient use of the data available. The method is illustrated with preliminary data on drinking status in adult twins. Although there is some bias in the ascertainment of male dizygous twins, the results suggest that monozygous twins are more concordant than dizygous twins for drinking status.

Alcohol Drinking↗
PubMed1977

Three statistical models for estimating length of stay.

The probability density functions implied by three methods of collecting data on the length of stay in an institution are derived. The expected values associated with these density functions are used to calculate unbiased estimates of the expected length of stay. Two of the methods require an assumption about the form of the underlying distribution of length of stay; the third method does not. The three methods are illustrated with hypothetical data exhibiting the Poisson distribution, and the third (distribution-independent) method is used to estimate the length of stay in a skilled nursing facility and in an intermediate care facility for patients enrolled in California's MediCal program.

California↗
PubMed2000

Aerosol Research and Inhalation Epidemiological Study (ARIES): air quality and daily mortality statistical modeling--interim results.

The Aerosol Research and Inhalation Epidemiological Study (ARIES) is an EPRI-sponsored project to collect air quality and meteorological data at a single site in northwestern Atlanta, GA. Seventy high-resolution air quality indicators (AQIs) are used to examine statistical relationships between air quality and health outcome end points. Contemporaneous mortality data are collected for Fulton and DeKalb counties in Georgia. Currently, 12 months of air quality and weather data are available for analysis, from August 1998 through July 1999. The interim mortality analysis used Poisson regression in generalized additive models (GAMs). The estimated log-linear association of mortality with various AQIs was adjusted for smoothed functions of time and meteorological data. The analysis considered daily deaths due to all nonaccidental causes, deaths to persons 65 years or older, and deaths in each of the two constituent counties. The fine particle effect associated with the four mortality subgroups, using only today (lag 0), yesterday (lag 1), 2-day average (average of today and yesterday), and first difference (today minus yesterday) measurements of the air quality relative to today's number of deaths was positive for lag 0, lag 1, and 2-day average and positive only for decedents at least 65 years of age using first difference. The t values ranged from 0.81 to 1.15 for lag 0, 1.04 to 1.53 for lag 1, 1.10 to 1.66 for 2-day average, and -0.32 to 0.33 for first difference with 346 or 347 days of data. No statistically significant estimate of the linear coefficient was found for the other 14 air quality variables in our interim analysis for the four mortality subgroups. We discuss diagnostics to support these models. These interim analyses did not include an evaluation of sensitivity to a larger set of lag structures, nonlinear model specifications, multipollutant analyses, alternative weather model and smoothing model specifications, air pollution imputation schemes, or cause-specific mortality indicators, nor did they include a full reporting of model selection or goodness-of-fit indicators. No conclusion can be drawn at this time about whether the findings from subsequent studies have sufficiently greater power to detect effects comparable to those found in other U.S. cities including at least 2 or 3 years of data.

Adolescent↗
PubMedDate not supplied

Statistical modelling in specific case analysis.

In spite of the problems associated with the development of a statistical approach in specific case analysis, the potential of two statistical methods, logistic regression and Bayesian belief networks, has been investigated and found encouraging in the context of a database relating to child murders with a sexual connotation. Continual collaboration between statisticians and detectives would be needed in the collection of the data, the choice and construction of the models, and the interpretation of the results.

Adult↗
PubMed1989

Statistical modelling of mitochondrial power supply.

By experiment and theory, formulae are derived to calculate the response of mitochondrial power supply, in flux and potential, to an ATP consuming enzyme load, incorporating effects of varying amounts of (i) enzyme, (ii) total circulating adenylate, and (iii) inhibition of the ATP/ADP translocase. The formulae, which apply between about 20% and 80% of maximum respiration, are the same as for the current and voltage of an electrical circuit in which a battery with potential, linear in the logarithm of the total adenylate, charges another battery whose opposing potential is also linear in the same logarithm, through three resistances. These resistances produce loss of potential due to dis-equilibrium of (i) intramitochondrial oxidative phosphorylation, (ii) the ATP/ADP translocase, and (iii) the ATP-consuming enzyme load. The model is represented geometrically by the following configuration: when potential is plotted against flux, the points lie on two pencils of lines each concurrent at zero respiration, the two pencils describing the respective characteristics of the mitochondrion and enzyme. Control coefficients and elasticities are calculated from the formulae.

Adenosine Triphosphate↗
PubMed1986

Statistical modelling of injury severity, with special reference to driver and front seat passenger in single-vehicle crashes.

First, the statistical analysis of injury severity is introduced by considering the following topics: Interpretation of the recorded grades of injury severity (e.g. fatal, serious, slight, none) as divisions of a continuous scale. The possible presence of errors in recording injury severity. How this is used in the statistical analysis of injury severity data, including discussion of computing methods. Secondly, attention is turned to data in which the severities of injury to two people in the same crash is given. British accident data for 1969-72 has been processed to give a cross-tabulation of the severity of injury to the driver and to the front seat passenger in four types of single-vehicle accidents (overturning and nonoverturning, each in rural and in urban areas). Three complications with this data are that the number of non-injury accidents is unknown, that the cases where a passenger was present but uninjured could not be distinguished from those where there was no passenger, and that there is inconsistency in the positioning of the thresholds separating serious from slight injury, and slight from no injury. A positive correlation between the severities of injury to the two occupants is evident in the data. This is interpreted as being largely due to the speed of the crash, and a model is developed in which the two severities jointly have a bivariate normal distribution.

Accidents, Traffic↗