Sentences with phrase «discriminant analysis of»

His multiple - discriminant analysis of Egyptian crania, carried out on an IBM 7090 computer at Harvard, was published in the Papers of the Peabody Museum in 1966.

Michael Crichton's multiple - discriminant analysis of Egyptian crania, carried out on an IBM 7090 computer at Harvard, was published in the Papers of the Peabody Museum in 1966

Not exact matches

For example, ancestral limbic systems mediate «long term» memory, i.e., meaning and experiential relations, whereas later evolved neocortical zones mediate the discriminant perception of external objects, i.e., the analysis of mental objects into (external) space.

To categorize companies on the basis of that information, Senn - Delaney used a statistical process that included frequency analysis, stepwise regression, and discriminant analysis.

To assess the relative similarity of core technologies, a Discriminant Functions Analysis was performed (Table7, Supporting Information S4).

Additionally, we support and expand upon the hypothesis that X inactivation is primarily driven by gene loss on the Y. Using linear discriminant analysis, we show that X-inactivation status can successfully classify 90 % of X-linked genes into those with functional or nonfunctional Y homologs.

Linear discriminant analysis achieved 92 % clinical classification accuracy, including 100 % separation of behavioural variant frontotemporal dementia and Alzheimer's disease.

Logistic discriminant function analysis for DIF identification of polytomously scored items

I also taught myself a fair bit of statistics along the way including logistic regressions and discriminant analysis in order to backtest different models for identifying outperformers, dividend growth / cuts etc..

We can also point out that, although in a limited way, discriminant analysis is a promising parameter to help in the classification of CHF, being necessary improvement and further studies on the subject.

The discriminant analysis has been used in several studies in the field of human medical cardiology.

As F - diameter was the most significant variable in each of the previous discriminant analyses, the strength of this variable alone as a diagnostic tool was investigated further.

However discriminant analysis could not always predict CM and syringomyelia status suggesting there are other anatomical or environmental factors which affect the development of these disorders.

Topics Include Exploratory Data Analysis, Multiple Regression, Logistic Regression, Correlation, Multivariate Analysis Of Variance (manova), Factorial Analysis Of Variance (anova), Factor Analysis And Principal Components, Discriminant Analysis, Structural Equation Modeling, And Emerging Data Analysis Techniques.

Analyses using the T1 dataset (N = 354) provided convergent evidence of validity with big - five personality traits and discriminant evidence with need for cognition.

Results highlighted a) through exploratory and confirmatory factor analyses, a meaningful six - factor model (emotion expression, task utility self - persuasion, help - seeking, negative self - talk, brief attentional relaxation, and dysfunctional avoidance); b) satisfactory internal reliabilities; c) test - retest reliability scores indicative of a satisfactory stability of the measures over time; d) preliminary evidence of convergent and discriminant validity with CERS - M being very weakly linked to verbal skill and moderately to emotion regulation strategies measured through the Flemish version of the COPE - questionnaire; e) preliminary evidence of criterion validity, with CERS - M scores predicting math anxiety, and to a lesser extent, students» performance; f) preliminary evidence of incremental validity, with the CERS - M predicting math anxiety and performance over and above emotion regulation measured by the COPE - questionnaire.

The purpose of this study was to evaluate the following: 1) the construct validity of the Meaning in Life Questionnaire (Steger et al., 2006), Greek Version using different explorative and confirmative factorial analysis approaches like Bifactor EFA, ICM - CFA, Bifactor CFA and ESEM; 2) the measurement invariance of MLQ across gender; 3) the internal consistency reliability of the MLQ; and 4) the convergent and discriminant validity of the MLQ with measures of well - being and mental distress.

More specifically, the objectives of this study are the following: 1) To validate the construct validity of the Meaning in Life Questionnaire (Steger et al., 2006), Greek Version using both exploratory and confirmatory factorial analysis techniques like Bifactor EFA, Bifactor CFA and ESEM; 2) to examine measurement invariance of MLQ across gender; 3) to study the internal consistency reliability of the MLQ; and 4) to evaluate the convergent and discriminant validity of the MLQ with the constructs of well - being, hope, anxiety, depression, stress, hope and resilience.

ABSTRACT: The purpose of this study was to evaluate the structure, invariance, reliability, convergent and discriminant validity of the MLQ with exploratory and confirmatory factor analysis in 1561 Greek adults.

A Comparison of Two Linear Discriminant Analysis Methods That Use Block Monotone Missing Training Data

The current series of meta - analyses have established the reliability and discriminant validity of disorganized infant attachment.

The forth block consisted of a previously developed search filter for finding studies on measurement properties [42], including terms like: «Psychometrics», «Validation Studies», «Internal consistency», «Discriminant analysis», «Factor analysis».

Results and Conclusion: Detailed exploratory and confirmatory factor analyses are presented from which the final items of the new questionnaires were chosen, for which he presents internal consistency estimates, convergent validity with similar measures, discriminant validity from social desirability, and incremental validity over similar constructs.

subjects) filled in the Ho Scale and the subscales «cynicism», «anger», and «type A» of the MMPI - 2 for an analysis of factorial and discriminant validity.

The discriminant analyses revealed that the procedure was effective at differentiating children displaying a clinical level of externalizing behavior from normally developing ones.

Weighted - average correlation coefficients between equivalent pairs of SDQ and Child Behavior Checklist subscales11 from 9 parent - reported studies were uniformly strong and positive (range: 0.52 < r < 0.71).10 Several studies showed strong correlations between SDQ subscales and «real world» outcomes such as clinical diagnoses (criterion validity); SDQ scores identified school - aged children with concurrent behavioral and emotional disorders, including attention - deficit / hyperactivity disorder (ADHD) and autism spectrum disorder / Asperger syndrome (ASD / AS), and predicted their occurrence 3 years later.4, 12,13 However, multitrait - multimethod analyses have not provided consistently strong evidence of discriminant validity of the school - age SDQ subscales.

Discriminant function analyses revealed that the groups differed only along one dimension, suggesting that parent and peer attachment served similar functions in terms of the adjustment indices measured.

Results highlighted a) through exploratory and confirmatory factor analyses, a meaningful six - factor model (emotion expression, task utility self - persuasion, help - seeking, negative self - talk, brief attentional relaxation, and dysfunctional avoidance); b) satisfactory internal reliabilities; c) test - retest reliability scores indicative of a satisfactory stability of the measures over time; d) preliminary evidence of convergent and discriminant validity with CERS - M being very weakly linked to verbal skill and moderately to emotion regulation strategies measured through the Flemish version of the COPE - questionnaire; e) preliminary evidence of criterion validity, with CERS - M scores predicting math anxiety, and to a lesser extent, students» performance; f) preliminary evidence of incremental validity, with the CERS - M predicting math anxiety and performance over and above emotion regulation measured by the COPE - questionnaire.

Prior to testing our hypotheses, we conducted a multilevel confirmatory factor analysis (CFA) to examine the discriminant validity of our research variables.

The SDQ's internal factor structure was assessed by using confirmatory factor analysis, with a series of competing models and extensions used to determine construct, convergent, and discriminant validity and measurement invariance over time.

Statistical analyses of the two age groups included: Pearson's correlations to explore the relationships among variables, Cluster Analysis to create groups with different levels of aggression, and finally discriminant analysis to determine which variables discriminate betweenAnalysis to create groups with different levels of aggression, and finally discriminant analysis to determine which variables discriminate betweenanalysis to determine which variables discriminate between groups.