The Classification of Depressive Illnesses

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).

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Psychotic and neurotic depression: discriminant function analysis and five-year outcome

Psychological Medicine ◽

10.1017/s003329170005100x ◽

1983 ◽

Vol 13 (2) ◽

pp. 373-383 ◽

Cited By ~ 26

Author(s):

J. R. M. Copeland

Keyword(s):

Discriminant Function ◽

Mental State ◽

Discriminant Function Analysis ◽

Hospital Care ◽

Catchment Area ◽

Function Analysis ◽

Depressive Illness ◽

Consecutive Series ◽

Case Record

SYNOPSISA consecutive series of 94 patients recently admitted to hospital from a defined catchment area and diagnosed as having a depressive illness were examined using standardized techniques for eliciting mental state, etc. The overlap between psychotic and neurotic diagnoses was 8·5% on discriminant function analysis of mental state items. A sub-sample of 71 patients was given a comprehensive postal and case record follow-up 5 years later. When patients developing organic and other complicating illnesses were excluded, those suffering from psychotic depression showed a significantly poorer outcome, as defined by relapse and required lengths of hospital care, than those diagnosed as suffering from neurotic depression.

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Classification of fish and non-fish acoustic tracks using discriminant function analysis

ICES Journal of Marine Science ◽

10.1093/icesjms/fsr198 ◽

2012 ◽

Vol 69 (2) ◽

pp. 313-322 ◽

Cited By ~ 1

Author(s):

Yunbo Xie ◽

Catherine G. J. Michielsens ◽

Fiona J. Martens

Keyword(s):

Discriminant Function ◽

Discriminant Function Analysis ◽

Function Analysis ◽

Fish Populations ◽

Fraser River ◽

Discriminating Power ◽

Sonar System ◽

Stationary Objects ◽

Individual Variables

Abstract Xie, Y., Michielsens, C. G. J., and Martens, F. J. 2012. Classification of fish and non-fish acoustic tracks using discriminant function analysis. – ICES Journal of Marine Science, 69: 313–322. Hydroacoustic data acquired for estimating fish populations contain information on both fish and non-fish targets, so sonar technicians traditionally rely on their knowledge of fish behaviour and experience with hydroacoustics to remove non-fish targets from the hydroacoustic data. This process is often labour-intensive and time-consuming, making real-time assessment of fish populations difficult. Simple solutions are not always available for all circumstances. However, the split-beam sonar data collected in the lower Fraser River, British Columbia, Canada, showed distinct signatures between actively swimming fish and non-fish objects such as drifting debris, surface bubbles, and stationary objects in the water column and off the river bottom. Acoustic tracks of fish and non-fish targets were characterized by differentiable statistical patterns that were amenable to discriminant function analysis (DFA). An application of DFA to segregate fish and non-fish targets detected by a split-beam sonar system in the lower Fraser River is presented, characteristics of user-identified fish and non-fish acoustic tracks being utilized as learning samples for the DFA. Also, a method to rank the discriminating power of individual variables is presented, providing guidance for constructing efficient and effective discriminant functions with variables that offer high discriminating power. The DFA yielded classification accuracies of 96% for fish and 91% for non-fish tracks and reduced the manual sorting time by 50–75%.

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

The International Journal of Neuropsychopharmacology ◽

10.1093/ijnp/pyz053 ◽

2019 ◽

Vol 22 (11) ◽

pp. 681-697 ◽

Cited By ~ 3

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.

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Academic Goal Profiles: A Comparison of Blind and Sighted Students

The Spanish Journal of Psychology ◽

10.5209/rev_sjop.2012.v15.n3.39395 ◽

2012 ◽

Vol 15 (3) ◽

pp. 1043-1054 ◽

Cited By ~ 2

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.

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Comparison of the Toy-Play Behavior of Autistic, Retarded, and Normal Children: A Reanalysis

Psychological Reports ◽

10.2466/pr0.1969.25.1.223 ◽

1969 ◽

Vol 25 (1) ◽

pp. 223-227 ◽

Cited By ~ 12

Author(s):

Barbara J. Weiner ◽

Donald R. Ottinger ◽

James R. Tilton

Keyword(s):

Discriminant Function ◽

Discriminant Function Analysis ◽

Function Analysis ◽

Measurement Instrument ◽

Important Variable ◽

Normal Children ◽

Observational Technique ◽

Toy Play ◽

Discriminant Function Analyses

Tilton and Ottinger (1964) examined differences among autistic, retarded, and normal children by observing their behavior in a toy-play setting. The purpose of this study was to reanalyze these data using a multiple discriminant function analysis, which allowed consideration of all 10 categories of toy play and their intercorrelations within one analysis. Significant differences ( p < .001) were found among the 3 groups and between the possible pairs of groups (normal-autistic, normal-retarded, autistic-retarded). In addition, information about the statistical classification of individuals was available. In the four discriminant function analyses, the proportions of Ss statistically classified the same as their original psychiatric diagnosis were .96 of the normals, .83 of the autistics, and .89 of the retardates. The combinational category of toy play emerged as the most important variable in discriminating the groups in all four analyses. It was concluded that this observational technique combined with the multiple discriminant function analysis would have practical utility as a diagnostic and evaluative measurement instrument.

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Classification of petroleum pollutants by linear discriminant function analysis of infrared spectral patterns

Analytical Chemistry ◽

10.1021/ac50011a041 ◽

1977 ◽

Vol 49 (3) ◽

pp. 500-502 ◽

Cited By ~ 16

Author(s):

James S. Mattson ◽

Carol S. Mattson ◽

Mary Jo. Spencer ◽

Frank W. Spencer

Keyword(s):

Discriminant Function ◽

Discriminant Function Analysis ◽

Function Analysis ◽

Linear Discriminant Function ◽

Linear Discriminant ◽

Infrared Spectral ◽

Spectral Patterns ◽

Linear Discriminant Function Analysis ◽

Petroleum Pollutants

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Attitudes toward Suicide among Attempters, Contemplators, and Nonattempters

OMEGA - Journal of Death and Dying ◽

10.2190/xg9y-1h7l-jhd7-vu86 ◽

1986 ◽

Vol 16 (4) ◽

pp. 325-334 ◽

Cited By ~ 30

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.

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Classification of rural households due to directions and types of outgoings

Wiadomości Statystyczne. The Polish Statistician ◽

10.5604/01.3001.0014.1021 ◽

2017 ◽

Vol 62 (8) ◽

pp. 53-73

Author(s):

Marlena Piekut

Keyword(s):

Statistical Methods ◽

Discriminant Function ◽

Discriminant Function Analysis ◽

Function Analysis ◽

Rural Households ◽

Analysis Data ◽

Multivariate Statistical Methods ◽

Multivariate Statistical ◽

Per Capita

The aim of the study is to isolate groups of rural households with similar outgoings and to describe them by socio-demographic and economic characteristics. It was carried out using multivariate statistical methods such as k-means cluster and discriminant function analysis. Data from the CSO survey of household budgets for the years 2004 and 2012 were used for the research purpose. The research resulted in the division of rural households into four groups considering the outgoings, where one group covered more than 2/3 of the households. Variables which discriminated the membership of rural households to certain groups to the largest extent were the number of people in the household and disposable income per capita.

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Quantitative Classification of Quartz by Laser Induced Breakdown Spectroscopy in Conjunction with Discriminant Function Analysis

Journal of Spectroscopy ◽

10.1155/2016/1835027 ◽

2016 ◽

Vol 2016 ◽

pp. 1-7 ◽

Cited By ~ 13

Author(s):

A. Ali ◽

M. Z. Khan ◽

I. Rehan ◽

K. Rehan ◽

R. Muhammad

Keyword(s):

Discriminant Function ◽

Discriminant Function Analysis ◽

Detection System ◽

Function Analysis ◽

Ambient Pressure ◽

Laser Induced Breakdown Spectroscopy ◽

Quantitative Classification ◽

Breakdown Spectroscopy ◽

Laser Induced Breakdown

A responsive laser induced breakdown spectroscopic system was developed and improved for utilizing it as a sensor for the classification of quartz samples on the basis of trace elements present in the acquired samples. Laser induced breakdown spectroscopy (LIBS) in conjunction with discriminant function analysis (DFA) was applied for the classification of five different types of quartz samples. The quartz plasmas were produced at ambient pressure using Nd:YAG laser at fundamental harmonic mode (1064 nm). We optimized the detection system by finding the suitable delay time of the laser excitation. This is the first study, where the developed technique (LIBS+DFA) was successfully employed to probe and confirm the elemental composition of quartz samples.

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