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Results for “Analysis of Variance”

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At least 19 recordsLinked to original sources
PubMed1977

Variance analysis of error in selected ion monitoring assays using various internal standards. A practical study case.

This study contains a practical application of variance analysis for the evaluation of precision in selected ion monitoring using stable isotope variants or chemically related compounds as internal standards. Variance analysis is applied to determine the relative contributions of the errors due to long-term and short-term effects of instrument stability. The technique allows the resolution of variance due to sample manipulation from that introduced by the gas chromatography mass spectrometry instrumentation. This provides an objective measure of potential internal standards. Evaluation of the dependency of these errors upon concentration indicates appropriate weighing factors to be applied for regression analysis.

Analysis of Variance↗
PubMed1979

Holy Cross Hospital, Chicago: cost variance analysis in a health care setting.

By knowing and understanding basic cost accounting techniques, administrators are better equipped to keenly judge their own institution's health care expenses. Managers who implement cost variance analysis are less likely to be forced into a defensive position with either board members or the general public.

Accounting↗
PubMed1978

[Study of statistical test connections in non-orthogonal analysis of variance].

In the Analysis of Variance, we quite often split up the model to test different hypotheses about the model. However, when we analyse the results, we must not forget that the statistics used for the tests are not stochastically independent, either for an orthogonal design, because the test statistics have the same denominator, or for non-orthogonal design. In the latter case, test statistics have not only the same denominator but also not-independent numerators. The links between test statistics have been studied for orthogonal designs (Dall'Aglio, 1962) and for symmetrical Incomplete Block Design (Ballas and Webster, 1966). We shall give here results for the general case of the Analysis of Variance, treat more particularly the case of the Incomplete Block Design and show the joint distribution of two test statistics and, more simply, their correlation coefficient.

Analysis of Variance↗
PubMed1977

[Repeated characterization, analysis of variance limitation and discrimination analysis classification of EEG-activity patterns in human sleep].

1. To describe quantitatively and to deliminate nine EEG sleep patterns, mean values and standard deviations of abundances of the frequencies 0.8 ... 1.8 c/sec, 2...3.5 c/sec, 4...13c/sec, 14 to 17 c/sec, 18 to 22 c/sec, and 23 to 40 c/sec as well as of the average amplitudes in selected frequency ranges were calaculated and the distributions represented. 2. All nine EEG activity patterns could be separated by means of univariate and multivariate analyses of variance on the basis of all 28 as well as the 17 indispensable variables. 3. In the course of a stepwise reduction of variables within the framework of a linear discriminant analysis an optimal set of 17 variables was determined for the separation of the patterns, comprising: the percent quantity of the frequencies 0.8 ... 3.5 c/sec, 7 ... 9 c/sec and 18 to 40 c/sec as well as the average amplitudes in the frequency ranges 0.8 to 3.5 c/sec and 7.5 to 40 c/sec. 4. By linear regression analyses it could be shown that the sleep scording system used, can be reflected on an interval scale with the aid of discriminant functions; this can be achieved on the basis of the optimal set of variables as well as of the five most indispensable variables. 5. Finally the degree of the objectivity of the scoring procedures was demonstrated. Advantages and disadvantages of sleep scoring systems were discussed and possibilities of the utilization of results suggested, also in respect to the further development of the automatic recognition of EEG activity patterns.

Analysis of Variance↗
PubMed1976

[Investigations on the Variability of the phasic pupillary light reflex (author's transl)].

Infrared pupillography was used to determine physiological time parameters of the direct phasic light reflex in 101 normal subjects. These parameters include latency, contraction and redilatation times as well as total reaction time, measured in response to 4 different light stimulus intensities. A total of more than 4000 pupillary stimulations in these subjects was analyzed statistically. The study of these time parameters included determination of the mean, the standard deviation and three dimensional analysis of variance, with the following results: 1. The physiological time parameters are bilaterally symmetrical. 2. The most stable parameters with least variability in an individual subject were latency and contraction time. The redilatation time, however, showed marked intra-individual variability. 3. Variance analysis revealed a high degree of correlation among the different parameters to light stimuli of varying intensity. 4. There was a highly significant prolongation of latency and of contraction time with increasing age. 5. No sex dependent effect on physiological time parameters was found. In addition, no interaction among light stimulus intensity, age and sex could be detected. Possible applications of the method for clinical neurological examination are discussed.

Adolescent↗
PubMed1979

An iterative algorithm for analysis of variance.

In this paper, an iterative algorithm is proposed for computing estimates of parameters and sums of squares in non-orthogonal multivariate analysis of variance, without inverting any matrix. It is useful in the case of a large design matrix for it saves memory and computation time. It was first proposed by Stevens (1948) for 3 factors and is here generalised to any number of factors and interactions of any order. Convergence properties are studied. The more orthogonal is the design, the faster is the convergence. Several examples are provided.

Analysis of Variance↗
PubMed1976

A managerial accounting analysis of hospital costs.

Variance analysis, an accounting technique, is applied to an eight-component model of hospital costs to determine the contribution each component makes to cost increases. The method is illustrated by application to data on total costs from 1950 to 1973 for all U.S. nongovernmental not-for-profit short-term general hospitals. The costs of a single hospital are analyzed and compared to the group costs. The potential uses and limitations of the method as a planning and research tool are discussed.

Accounting↗