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PubMed1999

Application of Bayesian inference to fMRI data analysis.

The methods of Bayesian statistics are applied to the analysis of fMRI data. Three specific models are examined. The first is the familiar linear model with white Gaussian noise. In this section, the Jeffreys' Rule for noninformative prior distributions is stated and it is shown how the posterior distribution may be used to infer activation in individual pixels. Next, linear time-invariant (LTI) systems are introduced as an example of statistical models with nonlinear parameters. It is shown that the Bayesian approach can lead to quite complex bimodal distributions of the parameters when the specific case of a delta function response with a spatially varying delay is analyzed. Finally, a linear model with auto-regressive noise is discussed as an alternative to that with uncorrelated white Gaussian noise. The analysis isolates those pixels that have significant temporal correlation under the model. It is shown that the number of pixels that have a significantly large auto-regression parameter is dependent on the terms used to account for confounding effects.

Artifacts↗
PubMed1983

Development of a radioimmunoassay data analysis pack (RIADAP) in level II basic for microcomputers.

A simple program written in Microsoft BASIC for the analysis of radioimmunoassay data is presented. The program was designed for use by unexperienced operators on a TRS-80 Model III microcomputer. Standard curve data are fitted by linear regression after a logit response/loge dose transformation. Standard errors of individual observations are computed, and confidence intervals are obtained for a critical t of 0.1. Standard observations are eliminated when they lie outside the confidence interval from the calculated response on the fitted curve, and this is accomplished until no datum can be eliminated or until the coefficient of determination reaches an operator defined value. The program then prints the regression parameters and the retained standard values. Unknown sample data can then be entered, and the values are computed relative to the final regression parameters of the standard curve. The values can be modified by operator defined correction/dilution factors. The mean value of the slope for 28 assays is -0.99, while the predicted theoretical slope with a loge transformation is -1. This program finds its greatest use in research laboratories where a number of different RIA are performed and where it is of value to have some control over the computation process.

Computers↗
PubMed1991

Level of measurement: key to appropriate data analysis.

While PACU nurses are increasingly conducting research studies to validate nursing practice, it is important to consider logical rules for data analysis. Level of measurement is an important consideration when selecting statistical tests to analyze the data. Statistical tests need not remain a mystery since level of measurement is the deciding factor for selecting which tests are appropriate for answering the research questions or testing the hypotheses.

Clinical Nursing Research↗
PubMed2000

Observations on the reproducibility and matching efficiency of two-dimensional electrophoresis gels: consequences for comprehensive data analysis.

Protein expression profiling by proteomics has the potential to be an ideal tool for the description of changes in complex biological systems or in the characterization of a disease. This study analyzes in more quantitative terms how methodological drawbacks of the current technology can hamper the comprehensive analysis of large sets of spot patterns by statistical means. Irreproducibilities in spot intensities due to silver staining and geometric distortions of the spot patterns inherent to the electrophoresis procedure push even the semiautomatic alignment and matching to their limits. This leads to reduced matching efficiencies for identical spots if no additional exhaustive manual matching is performed for every single spot in all gels. As a consequence, only a limited number of spots can be matched in all gels of a large set. The statistical pattern analysis of such data sets will thus not allow the comprehensive description of relevant pattern changes.

Electrophoresis, Gel, Two-Dimensional↗
PubMed2000

[Multimodal SPECT and MRT imaging data analysis for an improvement in the diagnosis of idiopathic Parkinson's syndrome].

Parkinson's disease (PD) is characterized by a degeneration of nigrostriatal dopaminergic neurons, which can be imaged with 123I-labeled 2 beta-carbomethoxy-3 beta-(4-iodophenyl) tropane ([123I]beta-CIT) and single-photon emission computed tomography (SPECT). However, the quality of the region of interest (ROI) technique used for quantitative analysis of SPECT data is compromised by limited anatomical information in the images. We investigated whether the diagnosis of PD can be improved by combining the use of SPECT images with morphological image data from magnetic resonance imaging (MRI)/computed tomography (CT). We examined 27 patients (8 men, 19 women; aged 55 +/- 13 years) with PD (Hoehn and Yahr stage 2.1 +/- 0.8) by high-resolution [123I]beta-CIT SPECT (185-200 MBq, Ceraspect camera). SPECT images were analyzed both by a unimodal technique (ROIs defined directly within the SPECT studies) and a multimodal technique (ROIs defined within individual MRI/CT studies and transferred to the corresponding interactively coregistered SPECT studies). [123I]beta-CIT binding ratios (cerebellum as reference), which were obtained for heads of caudate nuclei (CA), putamina (PU), and global striatal structures were compared with clinical parameters. Differences between contra- and ipsilateral (related to symptom dominance) striatal [123I]beta-CIT binding ratios proved to be larger in the multimodal ROI technique than in the unimodal approach (e.g., for PU: 1.2 vs. 0.7). Binding ratios obtained by the unimodal ROI technique were significantly correlated with those of the multimodal technique (e.g., for CA: y = 0.97x + 2.8; r = 0.70; P < 0.001). Concerning the correlations between SPECT data and clinical parameters, the significance levels in the multimodal ROI technique, for example, for the correlation between CA and the UPDRScom subscore (r = -0.49 vs. -0.32). These results show that the impact of [123I]beta-CIT SPECT for diagnosing PD is affected by the method used to analyze the SPECT images. The described multimodal approach, which is based on coregistration of SPECT and morphological imaging data, leads to improved determination of the degree of this dopaminergic disorder.

Adult↗
PubMed2001

Longitudinal data analysis: an application to construction of a natural history profile of Duchenne muscular dystrophy.

A 30-month prospective study of 27 Scandinavian boys with confirmed diagnosis of Duchenne muscular dystrophy was carried out to construct profiles of the natural history of the disease. Assessments which included measures of voluntary muscle strength and function were done at 3 monthly intervals except for the first and second which were separated by 1 month. Recently developed statistical methods for analysis of longitudinal data with repeated observations on the same individual were used avoiding the problem of induced serial correlations. This allowed for the construction of both reference and prediction profiles for the variables %MRC, motor ability, walking time for 10 m and the sum of myometry of seven muscle groups.

Child↗
PubMed1985

TWINAN: twin data analysis program for microcomputers.

A BASIC computer program designed to facilitate analysis of twin data is presented. The program estimates genetic parameters and tests their statistical significance based on the genetic and environmental hypothesis.

Computers↗
PubMed1985

Data analysis reveals significant microwave-induced eye damage in humans.

Appleton and McCrossan undertook a study for the U.S. Army at Ft. Monmouth to determine if microwave exposure would cause cataracts. They concluded: "The comparison showed the groups (microwave exposed vs. not exposed ) to be essentially the same and did not support the hypothesis that human cataracts are being caused by chronic exposure to microwaves in the military environment in this country." There are three major flaws in Appleton and McCrossan's work. First, the exposed group likely included people with little or no exposure. This would tend to minimize the possibility of finding microwave effects. Secondly, their control group consisted of people working with equipment known to cause eye damage. This also would tend to minimize the possibility of finding microwave effects. Thirdly, and most important, they did not do a statistical analysis on their data. When the writer did one, it was found that Appleton and McCrossan have a statistically significant difference between groups, with the microwave exposed showing more lens opacities than would be expected by chance. Thus, their conclusion should have been the opposite of what they stated. It is the uncritical acceptance of negative biological studies of non-ionizing radiation, such as this, that has contributed to the distortion of science in this area of research and has stimulated public opposition to the installation of such energy sources.

Adult↗
PubMed1982

[Automatic non-ambulatory measurement of arterial pressure. Computer data-analysis of the evaluation of antihypertensive treatment].

To gain a better understanding of the therapeutic effect of HTA, the present study reports a new method essentially based on the non invasive non ambulatory monitoring of blood pressure by the Dinamap 845. This apparatus was initially assayed towards the measure of invasive blood pressure and by the auscultatory method, and afterwards towards the analysis of approximately one hundred resulting data. The computer analysis of the data was performed using a microcomputer which gives the results as: time dependent curves over 24 hr; histograms, percentage of the values of HTA (above 140 mmHg for the systolic and 90 mmHg for the diastolic one); numeric data such as: average values, SEM... The method reported here appears to be convenient to follow new therapeutic treatment because the data obtained before and after treatment proved to be more rigorous and less varying upon the physician. This kind of investigation seems also helpful in the case of both hypertensive emergencies and treatment of those HTA which are difficult to stabilize. But it is thought to be not easily applied to all the hypertensions studied in the usual medical practise.

Blood Pressure Determination↗
PubMed1993

TopFit: a PC-based pharmacokinetic/pharmacodynamic data analysis program.

The program TopFit was developed and validated within the European pharmaceutical industry. It provides both pharmacokinetic data analysis support for international regulatory submissions of new drugs, and sophisticated techniques for model-based kinetic/dynamic evaluation during drug development. TopFit features are: (1) non-compartmental methods; (2) standard compartment models assembled from input and disposition modules; (3) a potentially unlimited number of linear user-defined models that accommodate metabolites, effects, and absorption profiles; (4) a library of 24 non-linear models. No user programming is required. A well-defined file structure allows ready exchange of data with other programs such as SAS. TopFit version 2.0 is now commercially available, with comprehensive documentation, in the form of an MS-DOS application for the PC.

Data Interpretation, Statistical↗
PubMed2006

Trends in off-label beta-blocker use: a secondary data analysis.

BACKGROUND: The off-label use of beta-blockers might be prevalent, but no studies have provided empiric data on the off-label use based on utilization data. OBJECTIVE: This secondary data analysis was conducted to describe the trends of off-label use of beta-blockers among ambulatory visits made to office-based physicians in the United States. METHODS: Data from the National Ambulatory Medical Care Surveys from 1999 to 2002 were used in this study. Physician visits at which beta-blockers were prescribed (beta-blocker visits) were included and classified as within-label or off-label visits according to whether an approved indication for the beta-blocker was coded for the visits. Variables of patient demographic characteristics, diagnosis, prescriber's specialty, and concomitant medication use were also analyzed. Logistic regression analysis was employed to investigate the potential determinants for the off-label use of beta-blockers. RESULTS: A total of 3349 million visits were made to office-based physicians during the study period. About 65% (2167 million) of all visits were prescribed with > or =1 medication (medication visits). Beta-blockers were prescribed in 5.9% (127.3 million) of all medication visits in the years 1999 to 2002. The 3 most frequently prescribed beta-blockers in this study were atenolol, metoprolol, and propranolol. The proportions of off-label use among beta-blocker visits were 44.3% (1999), 56.3% (2000), 62.3% (2001), and 46.9% (2002); overall, 52.0% (66.2 million). About 11% (75.7 million) of these off-label uses were prescribed to patients with concomitant conditions that required judicious use of beta-blockers. Specialists, such as cardiologists, were more likely to prescribe beta-blockers for off-label use than primary care physicians (odds ratio, 2.147; 95% CI, 2.1464-2.1473). CONCLUSIONS: Our study found that the off-label use rate of beta-blockers was higher than what has been previously reported for other diseases and medications. Compared with visits made to general practitioners, visits made to specialists were more likely to be prescribed off-label use of beta-blockers. Future studies are needed to understand the legal, economic, and clinical impact of off-label use.

Adrenergic beta-Antagonists↗
PubMed2003

2HAPI: a microarray data analysis system.

SUMMARY: 2HAPI (version 2 of High density Array Pattern Interpreter) is a web-based, publicly-available analytical tool designed to aid researchers in microarray data analysis. 2HAPI includes tools for searching, manipulating, visualizing, and clustering the large sets of data generated by microarray experiments. Other features include association of genes with NCBI information and linkage to external data resources. Unique to 2HAPI is the ability to retrieve upstream sequences of co-regulated genes for promoter analysis using MEME (Multiple Expectation-maximization for Motif Elicitation) AVAILABILITY: 2HAPI is freely available at http://array.sdsc.edu. Users can try 2HAPI anonymously with pre-loaded data or they can register as a 2HAPI user and upload their data.

Algorithms↗
PubMed1985

Data analysis of long-term blood pressure monitoring.

Long-term blood pressure monitoring provides a large quantity of data with a wide inter-individual or inter-group variability. The conventional "mean/standard deviation" approach to data analysis is a relatively insensitive instrument for detecting circadian differences in blood pressure profile, mainly because the mean and the variability around the mean are processed separately. The proposed Standardized Systolic and Diastolic Scoring (SSDS) method enhances the analytical possibilities. Preliminary evaluation of the SSDS method using data obtained in an anti-hypertensive drug trial suggests clinical relevance.

Ambulatory Care↗
PubMed2005

Microarray data analysis of mouse neoplasia.

Microarray gene expression analysis offers great promise to help us understand the molecular events of experimental carcinogenesis, but have such promises been fulfilled? Studies of gene expression profiles of rodent are being published and demonstrate that yes, indeed, gene array data is furthering our understanding of tumor biology. Recent studies have identified differentially expressed genes in rodent mammary, colon, lung, and liver tumors. Although relatively few genes on the rodent arrays have been fully characterized, information has been generated to better identify signatures of histologic type and grade, understand invasion and metastasis, identify candidate biomarkers of early development, identify gene networks in carcinogenesis, understand responses to therapy, and decifer overlap with molecular events in human cancers. Data from mouse lung, mammary gland, and liver tumor studies are reviewed as examples of how to approach and interpret gene array data. Methods of gene array data analysis were also applied for discovery of genes involved in the regression of mouse liver tumors induced by chlordane, a nongenotoxic murine hepatocarcinogen. Promises are beginning to be fulfilled and it is clear that pathologists and toxicologists, in collaboration with molecular biologists, bioinformatists,and other scientists are making great strides in the design, analysis, and interpretation of microarray data for cancer studies.

Animals↗
PubMed1976

Classification and discrimination for data analysis in pharmacology.

Classification and discrimination are described as methods of inference and decision-making in pharmacological data analysis. Principal components and multiple discriminant analysis are applied to animal and human spectra of the neuroleptics. A preliminary step is required to separate differences in potency from the spectral information.

Animals↗
PubMed2006

Classification tree method for bacterial source tracking with antibiotic resistance analysis data.

Various statistical classification methods, including discriminant analysis, logistic regression, and cluster analysis, have been used with antibiotic resistance analysis (ARA) data to construct models for bacterial source tracking (BST). We applied the statistical method known as classification trees to build a model for BST for the Anacostia Watershed in Maryland. Classification trees have more flexibility than other statistical classification approaches based on standard statistical methods to accommodate complex interactions among ARA variables. This article describes the use of classification trees for BST and includes discussion of its principal parameters and features. Anacostia Watershed ARA data are used to illustrate the application of classification trees, and we report the BST results for the watershed.

Animals↗
PubMed2003

Client-server environment for high-performance gene expression data analysis.

SUMMARY: We have developed a platform independent, flexible and scalable Java environment for high-performance large-scale gene expression data analysis, which integrates various computational intensive hierarchical and non-hierarchical clustering algorithms. The environment includes a powerful client for data preparation and results visualization, an application server for computation and an additional administration tool. The package is available free of charge for academic and non-profit institutions.

Computing Methodologies↗