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At least 73 records · Page 4Linked to original sources
PubMed1998

Statistical model of the hippocampal CA3 region II. The population framework: model of rhythmic activity in the CA3 slice.

A statistical model is given to describe the electrical activity patterns of large neural populations of the hippocampal CA3 region. A continuous model has been formalized to describe the statistical processes governing the interactions within and between neural fields. The system of partial differential equations contains diffusion terms which determine the evolution of second moments of the probability distribution functions. The model is supplemented with a differential description of post-synaptic potentials. The discretization procedure has been designed so as to make the discrete equations scaling invariant. Population activities as well as underlying single-cell voltages are simulated during normal and epileptiform activities in the hippocampal CA3 slice. It is demonstrated that our model can reproduce electrophysiological phenomena characteristic to both single-cell and population activities. Specifically, fully synchronized population bursts, synchronized synaptic potentials, and low amplitude population oscillation were obtained.

Action Potentials↗
PubMed1991

The FDG/PET methodology for early detection of disease onset: a statistical model.

The development of appropriate statistical methodologies for neuroimaging studies is dependent upon the research question of interest. Often studies are analyzed with techniques that may not be appropriate for the research question but are accepted owing to convention, familiarity, or apparent statistical sophistication. Neuroimaging data are particularly complex owing to (a) the high number of potential dependent variables (i.e., regions of interest) coupled with the practical limitations on sample size; (b) the known physical properties of scanners (e.g., resolution) interacting with the intricate and variable structure of the human brain; and (c) mathematical properties introduced into the data by the physiological model for quantification. In this article, a statistical model will be discussed for addressing a particular problem in clinical studies. Given that there is a characteristic abnormality in regional glucose metabolism in a specific disease, can a probabilistic statement be made with confidence regarding the likelihood of an individual scan being similar to those from the disease group or normal subjects? The model capitalizes on known statistical aspects of normal regional glucose metabolism. To illustrate the model, data will be presented on normal subjects, patients with confirmed Huntington's disease, and subjects at risk for the disease. Reliability and clinical validity of the model will be discussed.

Adult↗
PubMed1997

The dynamics of patient visits to a public hospital ED: a statistical model.

Using a public hospital's computerized database, we formulated a statistical model to explain emergency department (ED) patient volume for better staffing and resource allocation. All patients visiting the ED over a 3-year period were included in this retrospective study. Each observation described the total daily number of referrals and was defined by the following variables: day of the week, month of the year, holiday/ weekday, relative order in a 3-year sequence, and number of visits to the ED on that day. The statistical method used to build the model was analysis of covariance. Periodicity in average number of daily visits existed for each of the seasonal factors that were examined, repeating every year during the study period. Based on a graphic analysis, the model was defined and explained 65% of the variance during the 3-year study, with a relatively low standard deviation of error. A statistically significant correlation existed between time-related factors and the number of visits to the ED. This statistical model may prove to be of value for planning emergency services, which operate under stressful, unpredictable situations.

Analysis of Variance↗
PubMed1996

A statistical model of transmission of Hib bacteria in a family.

The simultaneous estimation of family and community transmission rates as well as cure rates from panel data in a recurrent Hib (Haemophilus influenzae type b bacteria) infection is considered. An individual-based stationary Markov process model with constant hazards in two age groups is applied to describe recurrent asymptomatic Hib infection in a family with small children. The problem of estimation is solved in terms of the Bayesian posterior of the model parameters. The model is used to predict prevalence and incidence of Hib carriage in families as a function of the family size and age structure.

Adult↗
PubMed1999

Potential for bias in estimating human fecundability parameters: a comparison of statistical models.

Fecundability studies, where couples attempting pregnancy subject to 'failure' (conception) one time in each menstrual cycle, present a natural discrete failure-time scenario. Because the biologic capacity to conceive varies among couples in the population, a complication arises in choosing a method of analysis, related to the fact that the maximum follow-up time can vary from study to study, and follow-up time could potentially have different effects on parameters based on different approaches to modelling. Traditional development in fertility studies has been based on an implicit assumption that binary outcomes for different menstrual cycles are mutually independent. We contrast traditional models to a random effects model where cycle viability is modelled as subject-specific. We clarify the interpretations for different parameters from different models. We show that the traditional approach yields some regression parameters that depend on follow-up time, limiting the generalizability of inferences based on this analytic approach. By contrast, the subject-specific model consistently estimates parameters of interest, if the underlying distribution is properly specified. Data from a fecundability study carried out in North Carolina serves to illustrate these points.

Bias↗
PubMed2000

Statistical models for longitudinal biomarkers of disease onset.

We consider the analysis of serial biomarkers to screen and monitor individuals in a given population for onset of a specific disease of interest. The biomarker readings are subject to error. We survey some of the existing literature and concentrate on two recently proposed models. The first is a fully Bayesian hierarchical structure for a mixed effects segmented regression model. Posterior estimates of the changepoint (onset time) distribution are obtained by Gibbs sampling. The second is a hidden changepoint model in which the onset time distribution is estimated by maximum likelihood using the EM algorithm. Both methods lead to a dynamic index that represents a strength of evidence that onset has occurred by the current time in an individual subject. The methods are applied to some large data sets concerning prostate specific antigen (PSA) as a serial marker for prostate cancer. Rules based on the indices are compared to standard diagnostic criteria through the use of ROC curves adapted for longitudinal data.

Algorithms↗
PubMed2000

Maternal serum screening for trisomy 18: assessing different statistical models to optimize detection rates.

We have evaluated three alternative models for trisomy 18 screening using the maternal serum markers alpha-fetoprotein (AFP) and intact human chorionic gonadotrophin (hCG). Using data from 46 affected pregnancies and 48 150 unaffected pregnancies, we calculated distribution parameters for AFP and hCG multiples of the median (MoMs) and the factor comprising AFP MoMxhCG MoM. The trisomy 18 risk at mid-trimester was then calculated using either bivariate analysis of AFP and hCG MoMs or univariate analysis of AFP MoMxhCG MoM. The observed detection rates and positive rates obtained using either published distribution parameters or those derived from the West Midlands population were compared for each model. Using fixed cut-offs for AFP and hCG of 0.66 and 0.40 MoMs resulted in a detection rate of 28.3% for a 0.5% false positive rate (FPR). Using published parameters, the univariate analysis model had a slightly higher detection rate of 32.6% for a 0.5% FPR (cut-off 1:248) compared to the bivariate model which was 28.3% (cut-off 1:239). Locally derived distribution parameters significantly improved the detection rate for the bivariate model for FPRs between 0.4-1.3% but worsened it below 0.4%. For the univariate model there was little difference in detection whether local or published parameters were used. Thus, we have confirmed that trisomy 18 screening using two markers can be a worthwhile addition to Down screening.

Chorionic Gonadotropin↗
PubMed2003

Multiple method comparison: statistical model using percentage similarity.

BACKGROUND: Method comparison typically determines how well two methods agree. This is usually performed using the difference plot model, which measures absolute differences between two methods. This is often not applicable to data with wide ranges of absolute values. An alternative model is introduced that simplifies comparisons specifically for multiple methods compared to a gold standard. METHODS: The average between a new method and the gold standard is represented as a percentage of the gold standard. This is interpreted as a percentage similarity value and accommodates wide ranges of data. The representation of the percentage similarity values in a histogram format highlights the accuracy and precision of several compared methods to a gold standard. The calculation of a coefficient of variation further defines agreement between methods. RESULTS: Percentage similarity histograms of several new methods can be compared to a gold standard simultaneously, and the comparison easily visualized through use of a single 100% similarity reference line drawn common to all plots. CONCLUSION: This simple method of comparison would be particularly useful for multiple method comparison and is especially applicable for centers collating for external quality assessment or assurance programs to demonstrate differences in results between laboratories.

Biometry↗
PubMed2002

Hierarchical statistical modelling of influenza epidemic dynamics in space and time.

An infectious disease typically spreads via contact between infected and susceptible individuals. Since the small-scale movements and contacts between people are generally not recorded, available data regarding infectious disease are often aggregations in space and time, yielding small-area counts of the number infected during successive, regular time intervals. In this paper, we develop a spatially descriptive, temporally dynamic hierarchical model to be fitted to such data. Disease counts are viewed as a realization from an underlying multivariate autoregressive process, where the relative risk of infection incorporates the space-time dynamic. We take a Bayesian approach, using Markov chain Monte Carlo to compute posterior estimates of all parameters of interest. We apply the methodology to an influenza epidemic in Scotland during the years 1989-1990.

Bayes Theorem↗
PubMed2002

Use of statistical models for evaluating antibody response as a correlate of protection against varicella.

In vaccine clinical trials, humoral antibody responses are often used to measure the effect of a vaccine because they correlate with a vaccine's protective efficacy against the target disease. While the concept of a correlate of protection usually refers to establishing a protective level of antibody titre, identifying a clear-cut value is often impossible because vaccine efficacy is not related solely to the antibody titre. We propose examining the relationship between disease protection and the whole distribution of antibody responses rather than a single cut-off level. In particular, we use failure-time models to estimate the relationship between long-term disease breakthroughs and primary antibody responses after vaccination. We apply these models to show that the varicella antibody response measured by glycoprotein enzyme-linked immunosorbent assay 6 weeks after vaccination strongly correlate with protection against varicella (chickenpox); we used 7-year follow-up data from children who received one dose of a live attenuated varicella (Oka/Merck) vaccine. In addition, we explore the potential use of these models to predict long-term disease breakthrough rates and to estimate the predicted vaccine efficacy of a similar varicella vaccine made with a modified manufacturing process.

Antibodies, Viral↗
PubMedDate not supplied

Statistical models appropriate for designs often used in group-randomized trials.

Group-randomized trials are characterised by the allocation of identifiable groups rather than individuals to study conditions; members within those groups are then observed to assess the effect of the intervention. It is convenient to categorize the designs employed in group-randomized trials along two dimensions, each with two levels. The first distinguishes between designs having just one or two time intervals and those having three or more intervals. The second distinguishes between nested cohort and nested cross-sectional designs. Following a brief review of the design and analytic issues common to group-randomized trials, and their general solutions, this paper presents the adaptations of the mixed-model analysis of covariance and random coefficients models that are required for the four combinations that result from this categorization scheme. The assumptions, strengths and weaknesses of each model are discussed.

Cohort Studies↗
PubMed2001

A statistical model for the evaluation of barrier contraceptive efficacy.

This paper describes an approach for the analysis of barrier contraceptive efficacy trials that accounts for timing frequency of intercourse and compliance. We allow exposure variables to vary for each act of intercourse and we control for timing of each act through a specific parametric function of the day of the act relative to the last day of the follicular phase of the cycle. The model can be used to examine the level of protection provided by a barrier versus no contraceptive method even when no control group of non-users is studied, as long as there are acts with no barrier use during the fertile window. We present results of a simulation study which examines performance of estimators and power under a variety of scenarios, including situations where an accurate benchmark for ovulation day is not available. As compared to the survival analysis approach commonly used in this setting, simulation results show that the new approach yields considerable gains in power to detect differences between the efficacy of contraceptive methods. An application to data from the FemCap versus diaphragm trial show results consistent with previous findings suggesting superiority of the diaphragm but also provides new evidence of the per act protection provided by both methods.

Biometry↗
PubMed1990

Analysis of gene-dosage effects on the expression of CD18 by trisomy 21 lymphoblastoid cell-lines using a statistical model to fit flow cytometry profiles.

It is not clear whether Down syndrome, the phenotypic expression of constitutional trisomy for chromosome 21 (T21), is the result of generalised disruption of homeostasis resulting from genetic imbalance, or the over-expression of specific genes on chromosome 21. In order to understand the effect of gene dosage more clearly, we have analysed the predicted and actual levels of expression of the leucocyte integrin beta subunit CD 18 on the surface of T21 leucocytes. Previous studies showed that CD18 expression by T21 lymphoid cell lines (LCL) is greater than on normal LCL. We have now developed a computer model that compares the observed and predicted CD18 flow cytometric profiles for trisomy 21 LCL. Three parameters (alpha, beta and gamma) have been defined that measure different aspects of gene dosage. Using the computer model to calculate these parameters, we have carried out a series of paired comparisons between normal and T21 LCL. The results show that, in some T21 LCL, increased CD18 expression is proportional to the existing gene dosage, in another set the effect is additive, whereas in others there is a combination of proportional and additive effects. The results suggest that gene regulation can exert pleiotropic effects on gene-dosage, and is consistent with a model in which gene dosage itself is the cause of disrupted homeostasis.

CD18 Antigens↗
PubMed2006

Statistical modeling of valley fever data in Kern County, California.

Coccidioidomycosis (valley fever) is a fungal infection found in the southwestern US, northern Mexico, and some places in Central and South America. The fungus that causes it (Coccidioides immitis) is normally soil-dwelling but, if disturbed, becomes air-borne and infects the host when its spores are inhaled. It is thus natural to surmise that weather conditions that foster the growth and dispersal of the fungus must have an effect on the number of cases in the endemic areas. We present here an attempt at the modeling of valley fever incidence in Kern County, California, by the implementation of a generalized auto regressive moving average (GARMA) model. We show that the number of valley fever cases can be predicted mainly by considering only the previous history of incidence rates in the county. The inclusion of weather-related time sequences improves the model only to a relatively minor extent. This suggests that fluctuations of incidence rates (about a seasonally varying background value) are related to biological and/or anthropogenic reasons, and not so much to weather anomalies.

Algorithms↗
PubMed2004

Explained variation and predictive accuracy in general parametric statistical models: the role of model misspecification.

When studying a regression model measures of explained variation are used to assess the degree to which the covariates determine the outcome of interest. Measures of predictive accuracy are used to assess the accuracy of the predictions based on the covariates and the regression model. We give a detailed and general introduction to the two measures and the estimation procedures. The framework we set up allows for a study of the effect of misspecification on the quantities estimated. We also introduce a generalization to survival analysis.

Female↗
PubMed1993

Predictions of resin-bonded bridge survivals, comparing two statistical models.

The purpose of this study was to compare the predictive accuracy of the standard Weibull distribution model with that of a modification, or mixture model, for resin-bonded etched-metal bridge survivals. A total of 189 bridges placed in adult patients treated by students and staff at a teaching hospital was evaluated over periods of up to 8 years. Survival predictions based on the actual survival data accumulated in 1989 were compared with the later survival data updated in 1992. Comparison of the two fitted Weibull predictive curves with the life table survival estimates from the 1992 updated data demonstrated clearly the improved accuracy of the mixture model for predicting survivals of the resin-bonded bridges in this study.

Denture, Partial, Fixed, Resin-Bonded↗