SEARCH · PubMed Health

Results for “Data analysis”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8Linked to original sources

PubMed1989

A procedure for data analysis of the rodent micronucleus test involving a historical control.

No standard procedure of data analysis for rodent micronucleus tests involving historical controls has been established. In the present paper, under the presumption that the distribution of the historical control is stable and reliable, a procedure with three statistical steps is proposed to analyze the frequency of micronucleated polychromatic erythrocytes (MNPCEs). In the first step, the frequencies of MNPCEs in negative and positive control groups of a current experiment of the micronucleus test are compared with the distribution of historical negative and positive controls to examine the technical validity of the current experiment. In the second step, the frequency of MNPCEs in each treatment group is compared with the distribution of the historical negative control. In the third step, the dose-response relation is tested with the Cochran-Armitage trend test. A Monte Carlo stimulation study shows that the power of this procedure is acceptable and also this procedure is robust. An application of this procedure on real data reveals that it is effective in detecting clastogenic chemicals when the probability of a type I error is nearly .01.

Animals↗

PubMed1989

Secondary data analysis: research method for the clinical nurse specialist.

This article presents a description of secondary data analysis and suggests that this type of research methodology may be helpful in facilitating research by the clinical nurse specialist (CNS). The article discusses the advantages and disadvantages of the use of this method specifically in relation to the CNS and offers suggestions for sources of data.

Data Collection↗

PubMed1993

Techniques to identify clinical contexts during automated data analysis.

The interpretation of automatically collected data to produce intelligent alarms and identify particular conditions is nearly impossible without identifying the specific context in which the data are obtained. Shifts in clinical context occur because of changes in the patient's physiologic state, or due to the passage of time, or due to changes imposed by therapeutic intervention such as surgery. Techniques to identify such changes in clinical context are discussed with particular attention to the application of cluster analysis, discriminant analysis, and statistical predictors. An example of these analyses applied to EEG data is presented, showing an unexpected hysteresis of EEG behavior in response to an hypoxic challenge.

Cluster Analysis↗

PubMed1981

Comparison of Ehrlich ascites tumour and mouse liver cells by analytical subcellular fractionation combined with a sensitive computational method for data analysis.

A simple method of analytical subcellular fractionation, combined with a sensitive computational method for data analysis and presentation, has been used to reinvestigate the distribution and relative amounts of several enzymes in the cytoplasmic and plasma membranes of two different cell types: one is a neoplastic, transformed cell type (Ehrlich ascites tumour cells), the other an untransformed, highly differentiated cell type (liver hepatocytes plus Kupffer and endothelial cells). In general the distribution of the enzymes in particular membranes is similar in the two cell types, however the relative amounts differ. Ehrlich ascites tumour cells have a higher specific activity of galactosyltransferase and ouabain-sensitive (Na,K)ATPase, while liver cells have higher glucose-6-phosphatase, 5'-nucleotidase and succinate dehydrogenase activity. These differences appear to be correlated with morphological and, in some cases, functional differences between the two cell types.

5'-Nucleotidase↗

PubMed1992

Seeing the forest despite the trees. The benefit of exploratory data analysis to program evaluation research.

In the present article, it is argued that there is a benefit to applying techniques of exploratory data analysis (EDA) to program evaluation. To exemplify this, an evaluation of a rehabilitation program for people with rheumatoid arthritis is presented. The perceived health status of patients receiving intensive rehabilitation services from a major rehabilitation institute was compared with that of patients receiving customary office-based care over an 18-month period. The data were analyzed in a conventional way (analysis of variance) and then by way of EDA techniques (graphic display of medians and boxplots). The conventional analysis suggested that all patients improved over time and that intensive rehabilitation services provided no particular benefit or harm. The exploratory analysis showed that the distribution of the outcome variable was patently nonnormal, thus casting doubt on the validity of the conventional analysis. The EDA further showed that the rehabilitation group lagged behind the comparison group for a year, with a precipitious improvement at the 18-month period. This suggests that a selection factor was operating (i.e., those in the rehabilitation group could have been sicker) or that the patients in the rehabilitation group were made more aware of their condition by the intensive health services they received. The EDA provided an important insight.

Analysis of Variance↗

PubMed1977

A simplified method of echocardiographic data analysis.

Rapid accurate analysis of echocardiographic data is accomplished using a sonic digitizer and programmable calculator. This method allows the echocardiographer to select technically optimal areas of the recording for analysis. The resolution of the measuring device is 0.1 mm. A hardcopy printout of both measurement and calculation is provided. Instead of expensive on-line computer, an inexpensive programmable calculator is used.

Computers↗

PubMed1990

A consultation system constructor for medical data analysis.

MAD is a system that helps an expert data analyst in a specific application domain (like epidemiology or image analysis) to build reasoning models aimed at fulfilling specific tasks. These models may be subsequently used to guide doctors in the analysis of a set of data referring to a specific ground domain. Expert knowledge is represented at various levels: a general description of an application domain and various models that formalize the reasoning followed to perform specific tasks within a defined application domain. Reasoning models are represented as rules of propositional calculus, and a meta-knowledge permits to support knowledge acquisition. During the consultation, different external programs may be run when needed, without the doctor having to learn how to use them. MAD is written in Golden Common LISP and may be linked to any external software for data analysis, provided it runs under MS-DOS and does not require more than 192 Kb. Examples of application of the system to epidemiology and image analysis are given.

Computer Simulation↗

PubMed1988

Late patency of the carotid artery after endarterectomy. Problems of definition, follow-up methodology, and data analysis.

To determine the relative incidence of recurrent carotid stenosis (RCS) and the effect of methodology on data analysis and interpretation, late results were obtained for 232 patients (270 procedures) from 1 to 51 months (mean 22 months) after carotid endarterectomy (group A). Patency of the carotid artery was confirmed by postoperative intravenous digital subtraction angiography (DSA) for most of the series, and a subset (subgroup A1) of 113 patients (129 procedures) also received DSA studies at later intervals of 4 to 49 months (mean 26 months). There were 23 late deaths and five late strokes. Only two of the strokes were ipsilateral to previous endarterectomy, and both of these patients had normal follow-up DSA studies. Late DSA imaging revealed either no RCS or only trivial defects (20% diameter or less) in 111 arteries, moderate (36% to 60%) RCS in nine, severe (70% to 90%) RCS requiring secondary procedures in eight, and internal carotid occlusion in one. Depending on the definition of RCS (secondary operation vs greater than or equal to 30% angiographic lesions), the cohort selected for analysis (group A vs subgroup A1), and the approach to calculations (crude vs cumulative), the incidence of recurrent stenosis after carotid reconstruction in this single study could be expressed within the extraordinary wide range of 3% to 32%. Although carotid endarterectomy was associated with uniformly low risk for late stroke, these results confirm that the reported recurrence rate may be substantially influenced by the method in which data are grouped and manipulated. Consistently presented data are essential to any comparisons concerning the surgical therapy for extracranial disease.

Actuarial Analysis↗

PubMed1997

A mixture model for duration data: analysis of second births in China.

In this paper we introduce a mixture model in which we combine logistic regression and piecewise proportional hazards models for analysis of duration data. The model allows simultaneous estimation of two sets of effects of covariates: one of the probability of an event and the other of the timing of the event. We illustrate the application of the model through an analysis of the effects of women's characteristics and of the acceptance of a one-child certificate on the birth of second children in China. Both factors affect the probability of having a second child, but only the acceptance of a one-child certificate has a significant and strong effect on the second-birth interval.

Algorithms↗

PubMed1992

Constrained and restrained refinement in EXAFS data analysis with curved wave theory.

This paper describes methods of constrained and restrained refinement of EXAFS data which provide a means of substantially reducing the number of independent parameters compared to conventional least-squares methods commonly used. Constrained refinement allows a major reduction in the number of free parameters for a refinement of a structural model. In restrained refinement, additional structural information from well-characterized small molecules is used to provide additional observations in the data analysis. Even though these methods are of general application to the majority of complex systems, they are particularly valuable for biological molecules. The methods are of major advantage for ligands where significant multiple scattering is present, e.g., histidine, tyrosine, CO, CN, etc. The bases of these methods are described, and applications to some complex chemical and biological systems are given.

Fetal Hemoglobin↗

PubMed1997

Application of neural networks to population pharmacokinetic data analysis.

This research examined the applicability of using a neural network approach to analyze population pharmacokinetic data. Such data were collected retrospectively from pediatric patients who had received tobramycin for the treatment of bacterial infection. The information collected included patient-related demographic variables (age, weight, gender, and other underlying illness), the individual's dosing regimens (dose and dosing interval), time of blood drawn, and the resulting tobramycin concentration. Neural networks were trained with this information to capture the relationships between the plasma tobramycin levels and the following factors: patient-related demographic factors, dosing regimens, and time of blood drawn. The data were also analyzed using a standard population pharmacokinetic modeling program, NON-MEM. The observed vs predicted concentration relationships obtained from the neural network approach were similar to those from NONMEM. The residuals of the predictions from neural network analyses showed a positive correlation with that from NONMEM. Average absolute errors were 33.9 and 37.3% for neural networks and 39.9% for NONMEM. Average prediction errors were found to be 2.59 and -5.01% for neural networks and 17.7% for NONMEM. We concluded that neural networks were capable of capturing the relationships between plasma drug levels and patient-related prognostic factors from routinely collected sparse within-patient pharmacokinetic data. Neural networks can therefore be considered to have potential to become a useful analytical tool for population pharmacokinetic data analysis.

Anti-Bacterial Agents↗

PubMed1977

Analog processing of vestibular nystagmus for on-line cross- correlation data analysis.

An analog processing circuit is described which allow accurate measurement of the phase relationships between input angular acceleration and resulting eye velocity. Vestibular nystagmic data are processed via analog technics to yield slowphase eye velocity. The turntable velocity input is cross-correlated with the eye velocity output, using a Nicolet MED-80 minicomputer system. The resulting correlograms are further processed to obtain precise phase information. Test data analysis shows a system resolution within 1 degree. Data from human and animal subjects are portrayed.

Acceleration↗

PubMed1995

Computer assisted data analysis in intensive care: the ICDEV project--development of a scientific database system for intensive care (Intensive Care Data Evaluation Project).

INTRODUCTION: Patient Data Management Systems (PDMS) for ICUs collect, present and store clinical data. Various intentions make analysis of those digitally stored data desirable, such as quality control or scientific purposes. The aim of the Intensive Care Data Evaluation project (ICDEV), was to provide a database tool for the analysis of data recorded at various ICUs at the University Clinics of Vienna. SETTINGS: General Hospital of Vienna, with two different PDMSs used: CareVue 9000 (Hewlett Packard, Andover, USA) at two ICUs (one medical ICU and one neonatal ICU) and PICIS Chart+ (PICIS, Paris, France) at one Cardiothoracic ICU. CONCEPT AND METHODS: Clinically oriented analysis of the data collected in a PDMS at an ICU was the beginning of the development. After defining the database structure we established a client-server based database system under Microsoft Windows NI and developed a user friendly data quering application using Microsoft Visual C++ and Visual Basic; RESULTS: ICDEV was successfully installed at three different ICUs, adjustment to the different PDMS configurations were done within a few days. The database structure developed by us enables a powerful query concept representing an 'EXPERT QUESTION COMPILER' which may help to answer almost any clinical questions. Several program modules facilitate queries at the patient, group and unit level. Results from ICDEV-queries are automatically transferred to Microsoft Excel for display (in form of configurable tables and graphs) and further processing. CONCLUSIONS: The ICDEV concept is configurable for adjustment to different intensive care information systems and can be used to support computerized quality control. However, as long as there exists no sufficient artifact recognition or data validation software for automatically recorded patient data, the reliability of these data and their usage for computer assisted quality control remain unclear and should be further studied.

Austria↗

PubMed1995

Longitudinal data analysis for linear Gaussian models with random disturbed-highest-derivative-polynomial subject effects.

For linear regression analysis of longitudinal data with Gaussian response, I propose a new model to generalize the traditional class of random effects models in which the random effects are deterministic polynomials with coefficients randomly distributed over subjects with mean zero. The generalization is accomplished by adding zero mean Gaussian 'disturbances' to the highest derivative of each random coefficient subject polynomial, independently at each observation time. The resulting random effects, which have mean zero at each observation time, are called disturbed highest derivative polynomials (DHDPs). The disturbances induce serial correlation and also allow the subject-specific DHDP time trends to be non-linear. I do not estimate the subject-specific DHDP time trends. Analysis is based on the marginal model, that is, the fixed effects or population model obtained by integrating the random polynomial coefficients and all disturbances out of the joint distribution of themselves and the response vector. This allows a 'population averaged' interpretation. One can select the DHDP order by an information criterion. When the population time trend is not correctly modelled, the optimal DHDP order will be larger than when it is correctly modelled. One can make the covariance matrix of the regression coefficients robust to errors in modelling the within-subject dependence. I describe the relationship of a DHDP to a smoothing polynomial spline, and show how to replace the DHDP model with a smoothing polynomial spline model for the within-subject dependence in the marginal model.

Bias↗

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↗

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↗