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

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.

Download Full-text

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%.

Download Full-text

The Classification of Depressive Illnesses

The British Journal of Psychiatry ◽

10.1192/s0007125000193195 ◽

1970 ◽

Vol 117 (538) ◽

pp. 241-250 ◽

Cited By ~ 102

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).

Download Full-text

Niche separation in coprophagous beetles: a comparison of two multivariate approaches

Bulletin of Entomological Research ◽

10.1017/s0007485300038724 ◽

1997 ◽

Vol 87 (6) ◽

pp. 625-631 ◽

Cited By ~ 10

Author(s):

P. Sowig

Keyword(s):

Discriminant Function ◽

Discriminant Function Analysis ◽

Function Analysis ◽

Niche Overlap ◽

Niche Separation ◽

Discriminant Functions ◽

Niche Space ◽

Advantages And Disadvantages ◽

Southwest Germany ◽

Discriminant Function Analyses

AbstractCoprophagous beetles (endocoprid and paracoprid Scarabaeidae, Hydrophilidae, and Staphylinidae) were extracted from 698 sheep droppings from a pasture in southwest Germany. To quantify the pairwise niche overlap of these species, pairwise discriminant function analysis was used to calculate the overlap of the discriminant distributions in a four-dimensional niche space. Niche separation was studied considering the following four factors: season (month) and macrohabitat when and where the dropping was deposited, dropping size, and water content of the dropping. Multiple discriminant function analysis was used to describe the distribution of species in a space defined by four discriminant functions. The first discriminant function was mostly influenced by the factor ‘season’. The importance of different factors for niche separation in different functional groupings of dung beetles is compared with results from the literature. Advantages and disadvantages of pairwise and multiple discriminant function analysis, and univariate evaluation methods are compared. The following problems and restrictions of discriminant function analyses are emphasized: (i) the usage of non-numerical variables; (ii) the calculation of niche breadths; (iii) failures, when bimodally distributed variables are considered; and (iv) the ecological interpretation of statistical significances.

Download Full-text

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

Download Full-text

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.

Download Full-text

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.

Download Full-text