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Results for “Models, Statistical”

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At least 739 records · Page 41Linked to original sources

PubMed2000

A statistical-mechanical model for regulation of long-range chromatin structure and gene expression.

In eukaryotic organisms, organization of chromatin is considered to play a role in transcriptional regulation by limiting the accessibility of a gene to the transcription machinery. It is not fully understood, however, how chromatin around a particular locus can be specifically altered to allow transcription. This paper introduces a statistical-mechanical model of chromatin to illustrate a potential mechanism. The model, which is mathematically equivalent to the one-dimensional Ising model of magnetic systems, explains how gene regulatory DNA sequences can affect the chromatin structure over a long distance in cis. The main assumption of the model is cooperativity of histone H1 in binding to the nucleosome array. This cooperativity results in a long-range correlation of histone H1 distribution along the chromatin. Due to this long-range correlation, a gene regulatory element, such as a transcriptional enhancer, may lead to depletion of histone H1 over a large region of chromatin thereby increasing the accessibility of the gene. The model provides a mechanism for a sensitive genetic switch and explains several aspects of gene regulation and chromatin structure.

Animals↗

PubMed2005

Conventional models overestimate the statistical significance of volume-outcome associations, compared with multilevel models.

OBJECTIVE: To compare the use of conventional statistical models with multilevel regression models in volume-outcome analyses of surgical procedures in an empirical case study. STUDY DESIGN AND SETTING: Using conventional regression models and multilevel regression models, we estimated the effect of hospital volume and surgeon volume on 30-day mortality and length of postoperative hospital stay in persons who had an esophagectomy, pancreaticoduodenectomy, or major lung resection for cancer in Ontario, Canada, from 1994 to 1999. RESULTS: The point estimates of volume-outcome associations were similar using either method; however, the 95% confidence intervals estimated by multilevel models were wider than those estimated by conventional models. A significant association between volume and mortality was identified in 2 of 18 (11%) comparisons using conventional analysis but in none of the 18 (0%) comparisons using multilevel analysis, and between volume and length of stay in 15 of 18 (83%) comparisons using conventional analysis and in 1 of 18 (6%) comparisons using multilevel analysis. CONCLUSION: Conventional and multilevel statistical models can yield substantially different results in the analysis of volume-outcome associations for surgical procedures.

Age Factors↗

PubMedDate not supplied

A statistical wisp model and pseudophysical approaches for interactive hairstyle generation.

This paper presents an interactive technique that produces static hairstyles by generating individual hair strands of the desired shape and color, subject to the presence of gravity and collisions. A variety of hairstyles can be generated by adjusting the wisp parameters, while the deformation is solved efficiently, accounting for the effects of gravity and collisions. Wisps are generated employing statistical approaches. As for hair deformation, we propose a method which is based on physical simulation concepts, but is simplified to efficiently solve the static shape of hair. On top of the statistical wisp model and the deformation solver, a constraint-based styler is proposed to model artificial features that oppose the natural flow of hair under gravity and hair elasticity, such as a hairpin. Our technique spans a wider range of human hairstyles than previously proposed methods and the styles generated by this technique are fairly realistic.

Acceleration↗

PubMed2006

Statistical methodologies in psychopharmacology: a review.

There has been a greatly increased interest in statistical methods in the psychiatric research and its applications over the past few decades, in parallel with advances in computers and statistical software. This review aims to describe the main topics related to statistical methods in psychopharmacology, namely nature of statistics in medicine, problems in data analysis, statistical modelling, developments in statistical technology, statistical reporting and meta-analysis.

Animals↗

PubMed2024

A statistical simulation model to guide the choices of analytical methods in arrayed CRISPR screen experiments.

An arrayed CRISPR screen is a high-throughput functional genomic screening method, which typically uses 384 well plates and has different gene knockouts in different wells. Despite various computational workflows, there is currently no systematic way to find what is a good workflow for arrayed CRISPR screening data analysis. To guide this choice, we developed a statistical simulation model that mimics the data generating process of arrayed CRISPR screening experiments. Our model is flexible and can simulate effects on phenotypic readouts of various experimental factors, such as the effect size of gene editing, as well as biological and technical variations. With two examples, we showed that the simulation model can assist making principled choice of normalization and hit calling method for the arrayed CRISPR data analysis. This simulation model is implemented in an R package and can be downloaded from Github.

CRISPR-Cas Systems↗

PubMedDate not supplied

Importance of total motile oval count in interpreting the hamster ovum sperm penetration assay.

A prospective study relating computer-assisted semen analysis (CASA) and technician-determined morphology to sperm penetration assay (SPA) outcome in patients with unexplained infertility or male factor was undertaken on 190 males aged 28-45 to determine the value of total motile oval count (TMO), compared to concentration, motility, and morphology considered independently, in predicting the outcome of the SPA. Prewash sperm count ranged 20-1,328 x 10(6), motility 0-93%, morphology 25-78% oval (%OVAL), and SPA scores 0-100%. Multiple regression analysis yielded two statistical models that identified significant predictors for % penetration (%P). Only TMO in one model and %OVAL in an independent effects model showed statistically significant correlation (P < 0.0001) to %P for all subjects. Discriminant function analysis showed the TMO model 85.4% accurate in classifying %P both in the abnormal range (< 20%P) and in the normal range (> or = 20%P). The independent effects model correctly classified 93% in the abnormal group, but projected 72 false negatives in the 101 subjects with %P > or = 20%, correctly classifying only 28.7%. Relative risk analysis showed TMO as a stronger risk factor affecting SPA outcome than %OVAL. It is concluded from this study that below 20%P, both TMO and %OVAL appeared to be comparable as predictive factors. Additionally, the TMO model was equally predictive for SPA > or = 20%P, where the independent effects model showed only 28.7% accuracy. SPA outcome appeared to be more profoundly affected by a decrease in TMO than by a decrease in %OVAL alone.

Adult↗

PubMed2004

Current issues in statistics and models for ecotoxicological risk assessment.

A review is given on statistical and modelling issues in ecotoxicology. The issues discussed are: 1. How to estimate an (almost) no effect concentration chemicals in the laboratory. 2. Combining single-species acceptable effect levels to an acceptable effect level for a multi-species ecosystem. 3. The combined effect of exposure to several chemicals. 4. Bioavailability in the natural environment and food-web models. Most current procedures in setting standards allow the environmental concentration to be above the acceptable effect concentration for a small fraction of the species. It is shown that a considerable part of the fraction of the affected species will suffer a severe effect.

Ecology↗

PubMed1982

Statistical molecular model for hydrated peptides. Application to angiotensin II analogs.

A statistical molecular model for hydrated peptides is used to stimulate the behaviour of various peptide chains in aqueous solution. The reliability of the model is ascertained by the evolution of the characteristic ratio, Cn, for hydrophobic and hydrophilic polypeptide chains, such as, respectively, poly-Ala and poly-Ser. The comparison of computed and experimental properties related to non radiative energy transfer of angiotensin II analogs, assuming that an ensemble of conformers is a satisfactory representation of the state of these molecules in water, provides further support for the model.

Amino Acid Sequence↗

PubMed1993

A statistical causal model for the assessment of dysarthric speech and the utility of computer-based speech recognition.

The evaluation of the degree of speech impairment and the utility of computer recognition of impaired speech are separately and independently performed. Particular attention is paid to the question concerning whether or not there is a relationship between naive listeners' subjective judgements of impaired speech and the performance of a laboratory version of a speech recognition system. It is a difficult task to relate a speech impairment rating with speech recognition accuracy. Towards this end, a statistical causal model is proposed. This model is very appealing in its structure to support inference, and thus can be applied to perform various assessments such as the success of automatic recognition of dysarthric speech. The application of this model is illustrated with a case study of a dysarthric speaker compared against a normal speaker serving as a control.

Adult↗

PubMed2005

Generating survival times to simulate Cox proportional hazards models.

Simulation studies present an important statistical tool to investigate the performance, properties and adequacy of statistical models in pre-specified situations. One of the most important statistical models in medical research is the proportional hazards model of Cox. In this paper, techniques to generate survival times for simulation studies regarding Cox proportional hazards models are presented. A general formula describing the relation between the hazard and the corresponding survival time of the Cox model is derived, which is useful in simulation studies. It is shown how the exponential, the Weibull and the Gompertz distribution can be applied to generate appropriate survival times for simulation studies. Additionally, the general relation between hazard and survival time can be used to develop own distributions for special situations and to handle flexibly parameterized proportional hazards models. The use of distributions other than the exponential distribution is indispensable to investigate the characteristics of the Cox proportional hazards model, especially in non-standard situations, where the partial likelihood depends on the baseline hazard. A simulation study investigating the effect of measurement errors in the German Uranium Miners Cohort Study is considered to illustrate the proposed simulation techniques and to emphasize the importance of a careful modelling of the baseline hazard in Cox models.

Cohort Studies↗

PubMed2004

A wave packet based statistical approach to complex-forming reactions.

A wave packet based statistical model is suggested for complex-forming reactions. This model assumes statistical formation and decay of the long-lived reaction complex and computes reaction cross sections and their energy dependence from capture probabilities. This model is very efficient and reasonably accurate for reactions dominated by long-lived resonances, as confirmed by its application to the C((1)D)+H(2) reaction.

Journal Article↗

PubMed2001

A three-dimensional regression model of the shoulder rhythm.

OBJECTIVE: The development of a thorax-fixed regression model for the shoulder which statistically predicts the orientation of the clavicle and the scapula from the humerus orientation. BACKGROUND: The application of three-dimensional position recording systems to the shoulder mechanism is limited to laboratory conditions. Studies in the field of ergonomics and sports require a method that can be applied in situ. It was found that the relation between the scapular and the humeral motions is consistent. In order to facilitate the biomechanical research on the shoulder a descriptive statistical model of the shoulder rhythm was developed. METHODS: The orientation of the shoulder bones of 10 subjects was determined in a large range of 23 humerus positions. The elbow was flexed in a splint and the arm was fully supported. The subjects exerted a 20 N external abduction and adduction force at the elbow in a plane perpendicular to the humerus. Other forces and moments were mechanically minimized. During the task the postures of the shoulder were recorded. The linear regression equations for the clavicular and scapular orientations were determined by means of a repeated measurements multi-variate analysis of variance for the co-variates: humerus orientation, initial orientation of the clavicle and the scapula, external force direction, gender and morphological characteristics of the subjects. RESULTS: The orientation of the clavicle and the scapula was predicted by five linear regression equations, including the co-variates: humerus orientation, external force direction and initial position. Morphology and gender did not significantly contribute to the clavicular and scapular orientation predictions. CONCLUSIONS: A statistical model is developed for the prediction of clavicular and scapular orientations, based on the humerus position, the initial posture and the direction of the external force. The model fitted well on an independent set of recorded position data for a different group of subjects. RELEVANCE: Morphological data of the shoulder girdle and gender did not significantly contribute to the model structure.

Biomechanical Phenomena↗

PubMed2006

Prediction of Lyme meningitis in children from a Lyme disease-endemic region: a logistic-regression model using history, physical, and laboratory findings.

BACKGROUND: Differentiating Lyme meningitis (LM) from other forms of aseptic meningitis (AM) in children is a common diagnostic dilemma in Lyme disease-endemic regions. Prior studies have compared clinical characteristics of patients with LM versus patients with documented enteroviral infections. No large studies have compared patients with LM to all patients presenting with AM and attempted to define a clinical prediction model. OBJECTIVE: To create a statistical model to predict LM versus AM in children based on history, physical, and laboratory findings during the initial presentation of meningitis. METHODS: Children older than 2 years presenting to the Alfred I. duPont Hospital for Children between October 1999 and September 2004 were identified if both Lyme serology and cerebrospinal fluid (CSF) were collected during the same hospital encounter. Patients were considered to have Lyme disease only if they met Centers for Disease Control and Prevention criteria (documented erythema migrans and/or positive Lyme serology). Patients were eligible for study inclusion if they had documented meningitis (CSF white blood cell count: >8 per mm3). Retrospective chart review abstracted duration of headache and cranial neuritis (papilledema or cranial nerve palsy) on physical examination and percent CSF mononuclear cells. Using logistic-regression analysis, the type of meningitis (LM versus AM) was simultaneously regressed on these 3 variables. The Hosmer-Lemeshow test was performed and the area under the receiver operating characteristic curve was calculated. RESULTS: A total of 175 children with meningitis were included in the final statistical model. Logistic-regression analysis included 27 patients with LM and 148 patients classified as having AM. Duration of headache, cranial neuritis, and percent CSF mononuclear cells independently predicted LM. The Hosmer-Lemeshow test revealed a good fit for the model, and the Nagelkerke R2 effect size demonstrated good predictive efficacy. Odds ratios based on the logistic-regression results were calculated for these variables. The final model was transformed into a clinical prediction model that allows practitioners to calculate the probability of a child having LM. CONCLUSIONS: Longer duration of headache, presence of cranial neuritis, and predominance of CSF mononuclear cells are predictive of LM in children presenting with meningitis in a Lyme disease-endemic region. The clinical prediction model can help guide the clinician about the need for parenteral antibiotics while awaiting serology results.

Child↗

PubMed1996

Statistical interaction model for exchangeability of food folates in rat growth bioassay.

The comparative value of several sources of dietary folate in promoting growth of folate-depleted rats was determined in a folate depletion-repletion rat growth bioassay. Folate-depleted rats were fed an amino acid-based diet supplemented with 11 different concentrations of folate (227, 272, 317, 363, 408, 454, 499, 544, 590, 635 and 680 nmol/kg) from each of 12 different sources of folate (folic acid, fried beef liver, cooked pinto beans individually, or as 1/3, 1/1, or 3/1 combinations of folate from the folic acid/beans, folic acid/beef liver and beans/beef liver) for a total of 132 treatments. Growth response to folic acid and bean folate was linear, whereas that to beef liver folate was distinctly nonlinear, beef liver folate being more potent at lower dietary concentrations but less potent at higher concentrations compared with folic acid and bean folate. Folic acid and bean folate were equivalent to and exchangeable with one another in promoting growth. Beef liver folate and folic acid/bean folate had an interactive effect in promoting growth. The nature of the interaction was antagonistic in that the presence of folic acid and/or bean folate reduced the efficacy of beef liver folate and vice versa. Beef liver folate is not exchangeable with either folic acid or bean folate. We conclude that food folates generally are not exchangeable and do interact adversely. A statistical interaction model that predicted the growth-promoting effect of several sources of dietary folate was developed and validated.

Animals↗

PubMed2005

Mixture model approach to tumor classification based on pharmacokinetic measures of tumor permeability.

PURPOSE: To categorize the disease severity of mammary tumors in an animal model through the application of a novel tumor permeability mixture model within a hierarchical modeling framework. MATERIALS AND METHODS: Thirty-six rats with mammary tumors of varying grade were imaged via dynamic contrast-enhanced (CE) MRI using albumin-(Gd-DTPA)30. Time-dependent contrast agent concentration curves for blood and tumor tissue were obtained and a mathematical model of microvascular blood-tissue exchange was developed under the hypothesis that endothelial integrity is disrupted in a manner proportional to the degree of malignancy, with benign tumors showing no disruption of the vasculature endothelium. This permeability model was incorporated into a statistical model for the benign and malignant tumor subgroups that enabled automatic subject classification. The structural and statistical models were implemented using the software Nonlinear Mixed Effects Modeling (NONMEM) to statistically separate subjects into the two subgroups. RESULTS: Individual tumor classifications (as benign or malignant) were evaluated against the Scarff-Bloom-Richardson microscopic scoring method as applied to the tumor histology of each subject. The model-based classification resulted in 90.9% sensitivity, 92.9% specificity, and 91.7% accuracy. CONCLUSION: Mixture model analysis provides a robust method for subject classification without user intervention and bias. Although the present results are promising, additional research is needed to further evaluate this technique for diagnostic purposes.

Animals↗

PubMed1990

Effects of common illnesses on infants' energy intakes from breast milk and other foods during longitudinal community-based studies in Huascar (Lima), Peru.

To assess the effects of common infections on dietary intake, 131 Peruvian infants were observed longitudinally. Home surveillance for illness symptoms was completed thrice weekly, and food and breast-milk consumption was measured during 1615 full-day observations. Mean (+/- SD) energy intakes on symptom-free days were 557 +/- 128 kcal/d (92.4 +/- 26.5 kcal.kg-1.d-1) for infants aged less than 181 d and 638 +/- 193 kcal/d (77.7 +/- 25.7 kcal.kg-1.d-1) for infants aged greater than 180 d. Statistical models controlling for infant age, season of the year, and individual showed significant 5-6% decreases in total energy intake during diarrhea or fever. There were no changes with illness in the frequency of breast-feeding, total suckling time, or amount of breast-milk energy consumed. By contrast, energy intake from non-breast-milk sources decreased by 20-30% during diarrhea and fever, and the small decrements in total energy consumption during illness were explained entirely by reduced consumption of non-breast-milk foods.

Age Factors↗

PubMedDate not supplied

[Analysis of intracranial pressure signals using artificial neural networks].

Intracranial pressure (ICP) is influenced by an array of predictable and unpredictable factors. Statistical modelling of this signal has only limited applicability because of the significant load of stochastic components. We tested the efficiency of an alternative approach, based on the methodology of artificial neural networks (ANNs) in the on-line prediction of future values of ICP and in the classification of signal properties. Satisfactory accuracy of forecasting was achieved with the ANNs for a 3-minute prediction horizon, while the prediction quality with autoregressive models of statistical origin was proved unsatisfactory. The results obtained with the ANNs were further improved when signal pre-processing with wavelet transform was employed. Nevertheless, even with the ANN methodology, no sudden breakdowns in the ICP signal (which in this respect might be compared to a "catastrophe") can be forecast with any practical applicability. We therefore applied two ANN algorithms, oriented at classification and discrimination of the global properties of the ICP signal. The neural network was expected to discriminate those sets of signal properties, which were assumed to correspond to certain clinical conditions of the patient. In a "dynamic pattern classification" the network was presented with several sections of ICP records. This was combined with information about the assignment of a given record to one of four arbitrary classes of danger. In this mode no data pre-processing was carried out, in contrast to our second approach, in which the signal was pre-processed with statistical analyses and only these intermediate coefficients were fed to the ANN classifier. The results obtained with both classification methods at their present stage of training were similar and approximated to a 70% rate of judgements consistent with expert scoring. Nevertheless, the method based on the assessment of global parameters of the ICP record seems more promising, because it leaves the possibility of extending the set of training data by information from other diagnostic modalities. The study aims towards the development of a pseudo-intelligent computer expert system, which has would be taught salient links between data extracted from the ICP signal and higher- order data, which contributed to the expert score. Hence the system would be able to make decisions on the basis of a reduced set of input information, available from a standard monitoring modality.

Algorithms↗

PubMed1991

Evidence for geographical variations in the prevalence of schizophrenia in rural Ireland.

Geographical variations in the rate of occurrence of schizophrenia have been the subject of much speculation and controversy, but it has proved extremely difficult to establish the existence of the phenomenon within a given study area. Using current inpatient and outpatient records and information from key informants active in the community, this study sought to identify all cases of schizophrenia in 36 District Electoral Divisions, constituting a clinical catchment area of 25,178 persons in a rural Irish county. Though the overall prevalence rate (3.3 per 1000) was unremarkable, this obscured a substantial and significant variation in prevalence rates (from 0.0 to 14.3 per 1000) between District Electoral Divisions. Prevalence rates in five District Electoral Divisions made particular contributions to the overall deviation from a statistical model for random occurrences in space. The results indicate spatial inhomogeneity in the prevalence of schizophrenia in rural Ireland and imply geographical variation in environmental or genetic factor(s) of etiologic relevance.

Adolescent↗