scholarly journals The fear of being laughed at: Individual and group differences in Gelotophobia

2008 ◽  
Vol 21 (1) ◽  
Author(s):  
Willibald Ruch ◽  
René T Proyer
Keyword(s):  
Factor Analysis ◽  
Case Studies ◽  
Discriminant Function Analysis ◽  
Group Membership ◽  
Function Analysis ◽  
Single Case ◽  
Group Differences ◽  
The Core ◽  
Social Partners ◽  
Cross Classification

AbstractSingle case studies led to the discovery and phenomenological description of Gelotophobia and its definition as the pathological fear of appearing to social partners as a ridiculous object (Titze 1995, 1996, 1997). The aim of the present study is to empirically examine the core assumptions about the fear of being laughed at in a sample comprising a total of 863 clinical and non-clinical participants. Discriminant function analysis yielded that gelotophobes can be separated from other shame-based neurotics, non-shame-based neurotics, and controls. Separation was best for statements specifically describing the gelotophobic symptomatology and less potent for more general questions describing socially avoidant behaviors. Factor analysis demonstrates that while Gelotophobia is composed of a set of correlated elements in homogenous samples, overall the concept is best conceptualized as unidimensional. Predicted and actual group membership converged well in a cross-classification (approximately 69% of correctly classified cases). Overall, it can be concluded that the fear of being laughed at varies tremendously among adults and might hold a key to understanding certain forms of humorlessness.

Acoustic Differentiation of Laryngeal, Esophageal, and Tracheoesophageal Speech

1984 ◽  
Vol 27 (4) ◽  
pp. 577-585 ◽  
Author(s):  
Joanne Robbins
Keyword(s):  
Speech Production ◽  
Principal Components ◽  
Discriminant Function Analysis ◽  
Group Membership ◽  
Function Analysis ◽  
Relative Importance ◽  
Vocal Rehabilitation ◽  
Tracheoesophageal Speech ◽  
Components Analysis ◽  
Temporal Measures

This investigation was designed to determine if a multivariate acoustic classifier could effectively discriminate group membership for 15 tracheoesophageal, esophageal, and laryngeal speakers. Seven intensity, 10 frequency, and 13 duration measures were quantified from recorded voice samples. Using principal components analysis, a subset of the 13 least redundant acoustic and temporal measures was systematically selected from the 30 original measures and analyzed singly and jointly in terms of its ability to discriminate among the three speaker groups. Discriminant function analysis revealed perfect categorization of the 45 subjects, indicating that the three methods of speech production are acoustically and temporally distinct from one another. The relative importance of the selected variables which, in combination, significantly differentiated the three groups is discussed in relation to physiologic differences among groups and clinical application for postlaryngectomy vocal rehabilitation.

scholarly journals Staging of Schizophrenia With the Use of PANSS: An International Multi-Center Study

2019 ◽  
Vol 22 (11) ◽  
pp. 681-697 ◽  
Author(s):  
Konstantinos N Fountoulakis ◽  
Elena Dragioti ◽  
Antonis T Theofilidis ◽  
Tobias Wikilund ◽  
Xenofon Atmatzidis ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Discriminant Function ◽  
Discriminant Function Analysis ◽  
Function Analysis ◽  
Analysis Of Covariance ◽  
Clinical Staging ◽  
Staging Model ◽  
Multi Center Study ◽  
Stage 1

Abstract Introduction A specific clinically relevant staging model for schizophrenia has not yet been developed. The aim of the current study was to evaluate the factor structure of the PANSS and develop such a staging method. Methods Twenty-nine centers from 25 countries contributed 2358 patients aged 37.21 ± 11.87 years with schizophrenia. Analysis of covariance, Exploratory Factor Analysis, Discriminant Function Analysis, and inspection of resultant plots were performed. Results Exploratory Factor Analysis returned 5 factors explaining 59% of the variance (positive, negative, excitement/hostility, depression/anxiety, and neurocognition). The staging model included 4 main stages with substages that were predominantly characterized by a single domain of symptoms (stage 1: positive; stages 2a and 2b: excitement/hostility; stage 3a and 3b: depression/anxiety; stage 4a and 4b: neurocognition). There were no differences between sexes. The Discriminant Function Analysis developed an algorithm that correctly classified >85% of patients. Discussion This study elaborates a 5-factor solution and a clinical staging method for patients with schizophrenia. It is the largest study to address these issues among patients who are more likely to remain affiliated with mental health services for prolonged periods of time.

The Classification of Depressive Illnesses

1970 ◽  
Vol 117 (538) ◽  
pp. 241-250 ◽  
Author(s):  
H. J. Eysenck
Keyword(s):  
Factor Analysis ◽  
Discriminant Function ◽  
Discriminant Function Analysis ◽  
Function Analysis ◽  
Good Deal ◽  
Depressive Illness ◽  
Statistical Techniques ◽  
History Of ◽  
Apparent Disagreement

As is well known, there has been a good deal of discussion about the unitary or binary nature of depression. Mapother (1926) and Lewis (1934) made a strong case for the unitary view on clinical grounds, Curran (1937) concurring. Kendell (1968) has reviewed the history of this argument; it is marred by confusion which has persisted through recent attempts to use statistical techniques of factor analysis and discriminant function analysis in an effort to find a more objective and empirical solution. It is the purpose of this brief note to draw attention to this confusion, to show how it has affected arguments of both adherents and opponents of the binary position, and to argue that the data are in fact in sufficient agreement to make possible a valid answer to both problems. It is suggested that the apparent disagreement between workers such as those of the Newcastle group (Kiloh and Garside, 1963; Carney, Roth and Garside, 1965) and the London (Maudsley) group (Kendell, 1968) is in fact quite irrelevant and is based on a misunderstanding of the statistical properties of factors, a misunderstanding apparently introduced in one of the first studies of this kind to be concerned with the problem of the classification of depressive illness, that by Hamilton and White (1959).

Academic Goal Profiles: A Comparison of Blind and Sighted Students

2012 ◽  
Vol 15 (3) ◽  
pp. 1043-1054 ◽  
Author(s):  
Francisco Pablo Holgado Tello ◽  
Leandro Navas Martínez ◽  
Irene Jover Mira
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Discriminant Function ◽  
Discriminant Function Analysis ◽  
Visually Impaired ◽  
Function Analysis ◽  
Goal Theory ◽  
Academic Goals ◽  
Visually Impaired Students

Based on academic goal theory, we compared the goals of visually impaired and sighted students. Participants included 171 students affiliated with ONCE (the National Spanish Organization for the Blind) and 163 sighted students, ranging from 8 to 27 years of age, who responded to the Spanish adaptation (González, Torregrosa, & Navas, 2002) of the goals questionnaire created by Hayamizu, Ito, and Yohiazaki (1989) and Hayamizu and Weiner (1991). Factor analysis indicated that goals varied among these students and that new ones arose in this study; furthermore, the model remained invariable regardless of students' status (visually impaired versus sighted). Cluster analysis revealed three distinct profiles in terms of academic goals, while discriminant function analysis suggested these profiles vary as a function of students' status (visually impaired versus sighted). It seems that visually impaired students hold more learning-oriented academic goals.

Assessing Abuse Among the Elderly Living in Public Housing

2000 ◽  
Vol 8 (1) ◽  
pp. 61-70 ◽  
Author(s):  
Linda E. Moody ◽  
Audrey Voss ◽  
Cecile A. Lengacher
Keyword(s):  
Factor Analysis ◽  
African American ◽  
Public Housing ◽  
Factor Structure ◽  
Discriminant Function Analysis ◽  
Elder Abuse ◽  
Function Analysis ◽  
The Elderly ◽  
Study Results ◽  
Elderly Living

Abuse and victimization among the elderly have received increased attention in the last few years from practitioners, researchers, and policymakers but remain growing problems, especially for elders who live in public housing. This study assessed the psychometric properties of an existing instrument, the Hwalek-Sengstock Elder Abuse Screening Test (HSEAST), which has been tested in only two studies. The instrument was administered to 100 African American, Hispanic, and White elders living in public housing. Study results were compared to findings from a previous study of elderly groups. A principal components factor analysis of the 15-item instrument supported the 3-factor structure for a total of 10 items (factor loadings = 0.4 or >), explaining 38% of the variance. A discriminant function analysis showed that 6 items were as effective as the 9-item model in classifying cases (71.4%) as abused.

Attitudes toward Suicide among Attempters, Contemplators, and Nonattempters

1986 ◽  
Vol 16 (4) ◽  
pp. 325-334 ◽  
Author(s):  
Mary Limbacher ◽  
George Domino
Keyword(s):  
Mental Illness ◽  
Factor Analysis ◽  
Discriminant Function ◽  
Discriminant Function Analysis ◽  
Function Analysis ◽  
Total Variance ◽  
Attitudes Toward Suicide ◽  
Significant Factors

The Suicide Opinion Questionnaire (SOQ) was administered to a sample ( N=738) of undergraduate volunteers, and responses were analyzed comparing attempters ( N = 35), contemplators ( N = 131) and nonattempters ( N = 483). A factor analysis indicated seven significant factors accounting for 24.2 percent of the total variance. A discriminant function analysis, using the seven factors, yielded two significant functions that discriminated respondents on the basis of sex and prior suicide history. The results are considered in the context of three issues (acceptability, lethality, and mental illness) important to the dynamics of suicide, and in terms of Goffman's theory of deviance.

scholarly journals Stock identification of tiger tooth croaker Otolithes ruber (Schneider, 1801) along the Indian coast using truss network analysis

2019 ◽  
Vol 66 (3) ◽  
Author(s):  
E.M. Chhandaprajnadarsini ◽  
Sushanta Kumar Chakrabortya ◽  
Subal Kumar Roul ◽  
Ashok Kumar Jaiswar ◽  
G.B. Sreekanth ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Network Analysis ◽  
Discriminant Function Analysis ◽  
Bay Of Bengal ◽  
West Coast ◽  
Arabian Sea ◽  
East Coast ◽  
Function Analysis ◽  
The West ◽  
Otolithes Ruber

The tiger toothed croaker Otolithes ruber (Schneider, 1801) of the family Sciaenidae is a demersal fish that contributes significantly to the marine landings of India. To identify stock units of O. ruber based on body shape morphometry, truss network analysis was carried out based on specimens collected from four selected locations, two each from east coast (Digha and Chennai along Bay of Bengal) and the west coast (Cochin and Ratnagiri along Arabian Sea) of India. A total of 20 truss distances along the fish surface, including head, mid body and posterior region were measured and transformed measurements were subjected to factor analysis and discriminant function analysis. The bivariate plot score of factor analysis indicating two distinct stocks on both the coasts may be the consequence of geographical isolation and different environmental conditions along the Bay of Bengal (east coast) and Arabian Sea (west coast). The Ratnagiri and Cochin population showed considerable mixing which indicated the presence of a unit stock along the west coast. However, existence of strong morphometric differentiation between Digha and Chennai populations indicated two separate spawning populations in the Bay of Bengal. In the cross-validation of Discriminant function analysis, the most well classified group was Digha population (97.85%). The present study suggests the possible existence of three stocks of O. ruber, one in west coast (Cochin and Ratnagiri) and two in east coast (Digha and Chennai) which can be considered while formulating effective management strategies for the species.

The Structure Among Measures of Personality, Social Attitudes, Values, and Social Norms

2007 ◽  
Vol 28 (4) ◽  
pp. 240-251 ◽  
Author(s):  
Lazar Stankov
Keyword(s):  
Factor Analysis ◽  
Individual Differences ◽  
Social Norms ◽  
Social Interactions ◽  
Correlation Matrix ◽  
Social Attitudes ◽  
Group Differences ◽  
Factor Scores ◽  
Ethnic Group Differences ◽  
Inside Out

Abstract. This paper presents the results of a study that employed measures of personality, social attitudes, values, and social norms that have been the focus of recent research in individual differences. These measures were given to a sample of participants (N = 1,255) who were enrolled at 25 US colleges and universities. Factor analysis of the correlation matrix produced four factors. Three of these factors corresponded to the domains of Personality/Amoral Social Attitudes, Values, and Social Norms; one factor, Conservatism, cut across the domains. Cognitive ability showed negative correlation with conservatism and amoral social attitudes. The study also examined gender and ethnic group differences on factor scores. The overall interpretation of the findings is consistent with the inside-out view of human social interactions.

Diagnoses Generated by Numerical Taxonomic Methods Applied to Standard Blood Variables

1980 ◽  
Vol 19 (04) ◽  
pp. 205-209
Author(s):  
L. A. Abbott ◽  
J. B. Mitton
Keyword(s):  
Liver Cirrhosis ◽  
Renal Disease ◽  
Principal Components Analysis ◽  
Discriminant Function ◽  
Principal Components ◽  
Discriminant Function Analysis ◽  
Chronic Renal Disease ◽  
Function Analysis ◽  
Infectious Hepatitis ◽  
Components Analysis

Data taken from the blood of 262 patients diagnosed for malabsorption, elective cholecystectomy, acute cholecystitis, infectious hepatitis, liver cirrhosis, or chronic renal disease were analyzed with three numerical taxonomy (NT) methods : cluster analysis, principal components analysis, and discriminant function analysis. Principal components analysis revealed discrete clusters of patients suffering from chronic renal disease, liver cirrhosis, and infectious hepatitis, which could be displayed by NT clustering as well as by plotting, but other disease groups were poorly defined. Sharper resolution of the same disease groups was attained by discriminant function analysis.

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