Discriminant Analysis Procedure Research Articles

Examining incubated and nonincubated startups from fear of failure and entrepreneurial well-being during crises

PurposeThis research aimed to examine entrepreneurial fear of failure and entrepreneurial well-being from the perspectives of incubated and nonincubated startups during crises.Design/methodology/approachData were collected by distributing online questionnaires to 152 respondents comprising 43 incubated and 109 nonincubated startups in Indonesia. A multivariate discriminant analysis procedure was used to examine the interrelationships between both groups at the discovery, validation, customer creation and construction stages.FindingsThe result showed a significant difference between these startups at various stages, which was analyzed to provide insights into the relevant dimensions of fear of failure for startups. The essence of entrepreneurial well-being during crises is in accordance with the role of business incubators in an emerging market economy.Practical implicationsStartups need to innovate in order to grow while considering other factors such as work-life balance and financial resource availability. This is important to ensure they have sufficient motivating dosage of fear of failure.Originality/valueThe present study evaluates incubated and nonincubated startups in an emerging market economy by using both the entrepreneurial fear of failure and well-being to capture possible differences between groups. The context of pandemic crises helps us formulate appropriate approaches taken by incubators and startups in the future crises.

Application of Discriminant Analysis to Predict Students’ Performances in Mathematics in Advanced Secondary Schools

This quantitative study aimed to use discriminant analysis procedures, to develop a classification model to be used for prediction, to predict students’ performances in Mathematics in advanced secondary schools in Tanzania. The study was conducted in Iringa Rural District to model students’ performances in Mathematics in advanced secondary schools owned by the government. Secondary data of students’ performances in Mathematics of 126 students when they were form five in the year 2020/2021 were collected from academic students’ progressive reports and three distinct groups each contained 42 students’ performances were formed. The analysis was done by using R programming software and a seed of 66 was used during the data partitioning to create training and test datasets. The maximum posterior probability rule was used as a classification rule to assign students’ performances in Mathematics into three proposed groups which are: High, Medium and Low. The classification accuracy achieved by the classification model to classify students’ performances in the training dataset is 97.33%. During validation, the model achieved the classification accuracy of 96.08% to classify students’ performances in the test dataset. These findings imply that, the classification model is valid and reliable. Hence the model is convenient to be used for prediction, to predict students’ performances in Mathematics in Advanced Certificate of Secondary Education Examinations.

Discriminant Analysis (DA) Technique for Identification Sex and Breed of Rabbits Depending on Morphological Traits

ABSTRACT Rabbits are a basic source of protein in many areas around the world. Rabbits are characterized by meat of good quality and high protein source. It is of importance to study and predict different rabbit characters. A total of 720 data values of three different breeds of rabbits (NewZeland White, Californian, and Rex) and both sexes were used. Discriminant analysis (DA) was used to classify the three rabbit breeds and genders based on the morphological characters (body length (BL), chest circumference (CHC), abdominal circumference (ABDC), thigh circumference (THC), ear length (EL) and ear width (EW)). Data were analyzed using the procedures of DA on SPSS 23 statistical package. The results were that ear width showed a strong participation (0.646) in discriminating the three breeds and explained most of the variance while body length (-0.608) was next in importance as a predictor followed by abdominal circumference (0.531) and the other variables were less contribution. Abdominal circumference is the most significant morphological trait as a discriminating variable (0.695) in discrimination between male and female and explained most of the variance followed by ear width (0.560) then the body length (-0.531). It is found that 59.2 % correct classification of the rabbit breeds using the discriminant functions was achieved and 70.8 % correct classification of the rabbit sexes using the discriminant functions was achieved.

Comparative Evaluation of Yield and Fruit Physico-Chemical Characteristics of Five Commercial Cultivars of Pomegranate Grown in Southeastern Italy in Two Consecutive Years

This study, conducted over two consecutive seasons (2018–2019), evaluates the yield and fruit physico-chemical traits of five commercial cultivars (‘Mollar’, ‘Dente di Cavallo’, ‘Acco’, ‘Jolly red’ and ‘Wonderful’) grown in the orchard at Foggia (Puglia region, southeastern Italy). The results show significant variations among the investigated cultivars for many measured parameters; seasons also significantly affected some data. As an average of the years, both ‘Dente di Cavallo’ and ‘Wonderful’ significantly showed the highest numbers (16.8 and 15.2, respectively) and weights (9.3 Kg, respectively) of fruit per tree. ‘Jolly red’ had the highest percentage of edible portions (58.5%), the most intense red color in juice (a* value, 11.7), a light-red skin color (despite its name) (a* value, 31.1) and the smallest fruits (26.7% of diameter ≤ 80 mm). Total soluble solids of all cultivars were considerable above the minimum value (12 °Brix) required for commercial use. ‘Wonderful’ significantly presented the highest value of juice acidity (2.5 g citric acid 100 mL−1) and the lowest MI value, and therefore it was classified as sour. Both ‘Dente di Cavallo’ and ‘Wonderful’ had significantly higher phenolic contents (591.0 and 519.1 mg 100 mL−1, respectively) than the other cultivars, while ‘Dente di Cavallo’ significantly showed the highest antioxidant activity value (6.4 mmol TE 100 L−1). The Stepwise Discriminant Analysis procedure allowed a significant differentiation among the cultivars. Correlation analysis showed a considerable relation among the different fruit traits. The present data are helpful in the selection of elite desirable pomegranate cultivars to be used for commercial production.

Imputation and system modeling of acid-base state parameters for different groups of patients

The paper investigated the possibility of correct replacement of missing values in sets of acid-base state in the artery and vein in different groups of patients with different outcomes of the disease: “discharged”, “died”, “transferred to another medical institution”, as well as prospects for the application of individual optimization multidimensional estimates of these biomedical parameters in the form of projections on a one-dimensional space. The relevance of the above tasks is determined by the need for the full use of medical data in the analysis of large repositories of information of medical organizations and the provision of verified multidimensional assessments of biomedical systems to doctors from a large range of patient health indicators. A statistical method has been applied to verify the correctness of imputation data sets using discriminant analysis procedures. Further, the imputed data set was processed to obtain a symmetric correlation matrix optimized in a certain way and the accompanying logarithms of criterion functions that are individual system assessments of the condition of each patient in different groups of patients at a certain point in the study. After that, to identify differences in the logarithms of the criterion functions of the acid-base state parameters between groups of patients with different outcomes, the authors used the method of calculating multidimensional Hotelling T2 statistics. The correctness of the application of discriminant analysis procedures to verify the imputation of data sets is shown. Differences in the logarithms of the criteria functions of the acid-base state indicators between venous and arterial blood by patient outcome groups were revealed. Significant differences in the parameters of acid-base state based on the multidimensional statistics of T2 Hotelling between groups of patients with different outcomes were revealed. It is found that data imputation significantly increases the volume and representativeness of the sample under study. It is demonstrated that the substituted data make it possible to carry out a systematic statistical assessment of the totality of body parameters based on the calculation of the logarithms of the criterion functions of the acid-base state. Such logarithms make it possible to reliably distinguish patients in different groups of patients by outcomes in three groups: “discharged”, “deceased”, “transferred to another medical institution”. 100 % differences of biochemical parameters according to the multivariate T2 Hotelling statistics between these three groups of patients with COVID-19 are shown. The results of the study can be applied in the development of information systems of individual medical biochemical and hematological devices and analyzers and corresponding artificial intelligence systems in the future.

Repeated measures discriminant analysis using multivariate generalized estimation equations.

Discriminant analysis procedures that assume parsimonious covariance and/or means structures have been proposed for distinguishing between two or more populations in multivariate repeated measures designs. However, these procedures rely on the assumptions of multivariate normality which is not tenable in multivariate repeated measures designs which are characterized by binary, ordinal, or mixed types of response distributions. This study investigates the accuracy of repeated measures discriminant analysis (RMDA) based on the multivariate generalized estimating equations (GEE) framework for classification in multivariate repeated measures designs with the same or different types of responses repeatedly measured over time. Monte Carlo methods were used to compare the accuracy of RMDA procedures based on GEE, and RMDA based on maximum likelihood estimators (MLE) under diverse simulation conditions, which included number of repeated measure occasions, number of responses, sample size, correlation structures, and type of response distribution. RMDA based on GEE exhibited higher average classification accuracy than RMDA based on MLE especially in multivariate non-normal distributions. Three repeatedly measured responses namely severity of epilepsy, current number of anti-epileptic drugs, and parent-reported quality of life in children with epilepsy were used to demonstrate the application of these procedures.

Penalizing ordered and multinomial likelihood functions with prior information for discrete choice modeling of consumer demand

This research note extends Bayesian discriminant analysis procedures to the ordered and multinomial logistic likelihood functions. Use of the procedure is warranted when the researcher desires to identify the membership of individuals randomly drawn from distinct groups or locations in a population, rather than from a random sample of undifferentiated individuals from a population. An empirical application analyzes consumers’ reasons why they choose to support a beef product produced with enhanced pasture management practices.

Employer and employee perspectives of HRM practices within SMEs

ABSTRACT This paper examines the perspectives of employers and employees within nano, micro, small, medium, and large firms in relation to HRM practices. The study draws upon a large sample of respondents from firms of all size categories. An online questionnaire comprising established HRM measures was used to collect the data. A multivariate discriminant analysis procedure was used to identify the interrelationships between the employer and employee groups, across firms by size, and how they viewed the importance of the HRM measures. The study found a strong congruence between employers and employees across most constructs and provides insights into the role firm size plays in the formalization of HRM practices and the relative importance of such factors within SMEs.

Discriminant analysis with mixed non normal variables

The mixed variable discriminant analysis procedure assumes that observations are distributed multivariate normal with different group means but same variance-covariance matrix. However, attention has not been given in discriminant analysis when the assumption of normality no longer holds. Therefore, we present a simple but new approach to mixed variable discriminant analysis when available observations (or its mixture) are not distributed multivariate normal. Specifically, a mixture of bernoulli and exponential and, poisson and bernoulli variates in discriminant analysis were presented in this work. Under a given condition, the suggested mixed non normal discriminant procedure demonstrated ability to allocate a mixture of non normal observations with minimal error.

Diversity of biometric and morphological traits among sheep breeds in Nigeria

Towards assessment of variations within and between sheep; biometric and morphological data of the four breeds of sheep found in Nigeria were collected using multi-stage samplin method. A total of 46 Balami, 30 Uda, 36 Yankasa and 37 WAD were sampled. Stepwise multiple regression procedure was used to find the best linear combination of metric variables that best predict the body weight. Principal component analysis of biometric and morphological traits was carried out. Simple discriminant analysis procedure was used to classify the breeds. Cluster analysis was done using the model building specificationinterface. Head length (HL), chest girth (CG), leg length (LL), and tail length were the only linear body measurements that were significant (P<0.01) in predicting body weight of sheep in the overall prediction equation. Body weight and all the linear body measurements had their highest loadings on principal component 1 (PC1). Tassel was the only variable that had its highest loading on PC2. Tail type and state (location) were the variables that bestdescribes the third component (PC3). Sex and hair type were variables that best described the forth component (PC4). Discriminant analysis showed that 70.59% of sheep sampled as Balami were classified as pure breed. Sheep sampled as WAD and Yankasa had 100% conformation while Balami and Uda had 70.59% and 60%, respectively in conformation to the classifying features of their breed based on discriminant analysis. The farthest genetic distance (5.48) was observed between Balami and WAD while the shortest genetic distance (1.26) was observed between Balami and Uda. Improvement of growth traits of sheep breedsin Nigeria is recommended through the use of either Balami or Uda as sire and either WAD or Yankasa as dam.

Multivariate statistical analysis of stable isotope signatures and element concentrations to differentiate the geographical origin of retail milk sold in Singapore

Singapore's reliance on imported foods makes the country susceptible to food fraud and food safety related incidents. To ensure authenticity of food source and indirectly food quality and safety, the development of an independent system that can trace the origin of a food is important to compliment the existing paper-based approach. A scientific approach to food traceability using isotope ratio and element concentration measurements was demonstrated using dairy milk as an example matrix. An iterative stepwise linear discriminant analysis procedure applied to the isotope ratios and element concentrations of 57 milk samples separated them into their six different country of origins. Si, Se, Li, B, Rb, Ba, P, Mn, Mo, Pb and the δ13C and δ15N of the defatted milk casein were found to be the key parameters providing maximum discrimination. The model was successfully evaluated with a blind-test, comprising of 10 samples with origins unknown to the analysts.

Genetics of Arthrogryposis and Macroglossia in Piemontese Cattle Breed.

Simple SummaryThe study was carried out in order to investigate the genetic background of arthrogryposis and macroglossia in the Piemontese cattle breed, for which limited information is available so far. The genotyping of affected and healthy animals with a high-density chip and the subsequent genome-wide association study did not evidence a single strong association with the two pathologies. Therefore, for arthrogryposis, the results do not support the existence of a single-gene model, as reported for other breeds. Rather, 23 significant markers on different chromosomes were found, associated to arthrogryposis, to macroglossia, or to both pathologies, suggesting a more complex genetic mechanism underlying both diseases in the Piemontese breed. The significant single nucleotide polymorphisms (SNPs) allowed the identification of some genes (NTN3, KCNH1, KCNH2, and KANK3) for which a possible role in the pathologies can be hypothesized. The real involvement of these genes needs to be further investigated and validated.Arthrogryposis and macroglossia are congenital pathologies known in several cattle breeds, including Piemontese. As variations in single genes were identified as responsible for arthrogryposis in some breeds, we decided: (i) to test the hypothesis of a similar genetic determinism for arthrogryposis in the Piemontese breed by genotyping affected and healthy animals with a high-density chip and applying genome-wide association study (GWAS), FST and canonical discriminant analysis (CDA) procedures, and (ii) to investigate with the same approach the genetic background of macroglossia, for which no genetic studies exist so far. The study included 125 animals (63 healthy, 30 with arthrogryposis, and 32 with macroglossia). Differently from what reported for other breeds, the analysis did not evidence a single strong association with the two pathologies. Rather, 23 significant markers on different chromosomes were found (7 associated to arthrogryposis, 11 to macroglossia, and 5 to both pathologies), suggesting a multifactorial genetic mechanism underlying both diseases in the Piemontese breed. In the 100-kb interval surrounding the significant SNPs, 20 and 26 genes were identified for arthrogryposis and macroglossia, respectively, with 12 genes in common to both diseases. For some genes (NTN3, KCNH1, KCNH2, and KANK3), a possible role in the pathologies can be hypothesized, being involved in processes related to muscular or nervous tissue development. The real involvement of these genes needs to be further investigated and validated.

Face Classification in Adults and Minors, an Approach based on Facial Anthropometry

The process of age estimation is a task of computer vision that represents a challenge to the diverse factors that influence the process of aging in humans such as environment, food, and toxic habits, among others. Such a task has been studied from different approaches. In this work, a geometric approach is developed by using distances and proportions existing in every face. The functionality is increased by the use of fiducial points to locate any characteristic features of the face; its location is based on craniofacial growth studies used in the area of forensic anthropometry and plastic surgery. The location of 15 fiducial points is considered through the ASM algorithm and 8 distances between fiducial points, which statistically verify the difference in facial proportions between adults and minors. The distances obtained are analyzed with the Discriminant Analysis procedure to study the correlations between distances and the corresponding age group. From this, a model that allows classifying a new image in an age group is constructed: adults; those over 18 years of age, and minors; those under 17 years of age, obtaining 90% accuracy.

Phenotypic characteristics and comparative evaluation of preserved animals from Lithuanian pig breeds

The aim of the study was phenotypic characterization and comparative evaluation of Lithuanian Indigenous Wattle and Lithuanian White pigs. Physical measurements were taken only from a representative set of adult animals: sows and boars. Evaluation of breeds included discrete (qualitative) and quantitative variables and was performed according to the Guidelines of FAO for Phenotypic Characterization of Animal Genetic Resources. The data were subjected to the analysis of variance in general linear (GLM) and discriminant analysis procedures in SPSS 17. The qualitative characterization of preserved animals validated the characteristics of Lithuanian pig breeds described in old literature. The comparative evaluation of the physical measurements of Lithuanian White and Lithuanian Indigenous Wattle pigs showed the highest significant differences in body, ear and tail length. Due to the different physiological status of females the statement that Lithuanian White pigs are larger animals than Lithuanian Indigenous Wattle pigs better confirms the weight and body dimensions of males. Small differences in body dimensions were found only between the youngest animal groups under 24 months of age and older animals. However, the results of the canonical discriminant analysis did not give any evidence that pigs of different age have different characteristics.

121 Non-invasive monitoring of hot-iron brands on growing cattle

Abstract Hot-iron branding is a traditional form of permanent cattle identification that produces a scar. There is a need for science-based determination of cattle brand age through non-invasive monitoring of the healing process. Near infrared reflectance spectroscopy (NIRS) has been used by medical forensic scientists to obtain such information. Healing of cutaneous injury involves inflammatory (1 to 3 d), proliferative (4 to 21 d), and remodeling (22 to 365 d) phases. Collagen changes as burn scars mature, i.e. there is an increase in the Type I/ Type III collagen ratio compared to normal skin. The altered ratio is evident in a transformation of collagen from a basketweave arrangement to small parallel bundles. During the remodeling phase, due largely to the Type I/III collagen ratio, scar tissue becomes visibly different than un-injured skin. Previous research has examined the differences in hot-iron brands applied to nursing (~30 d old) Bos taurus cross calves at 0, 33, and 153 d post-branding. Our objective was to continue this research by obtaining near infrared spectra (11001700nm) on hot-iron brands applied to 15 weaned (~ 270 d old; 238 ± 7kg) Bos taurus cross steers at 21, 32, and 51 d post-branding. Spectra were obtained on branded (n = 3) and unbranded (n = 3) skin tissue from each animal, each date. Hair was clipped to < 5mm on unbranded skin. Spectra were analyzed as log 1/reflectance with 1st derivative and scatter correction applied. Linear discriminant analysis and regression procedures were applied to distinguish between brand treatment and date post-branding. Spectra from branded and unbranded skin were correctly (P < 0.05) identified at ~95%. Brand age was predicted successfully (P < 0.05) but not accurately enough for forensic application (RSQ = 0.50; RMSE = 9.75 d). The NIRS technique can discriminate differences in the age of cattle brand scars but numerical prediction requires further investigation.

Combining E-Nose and Lateral Flow Immunoassays (LFIAs) for Rapid Occurrence/Co-Occurrence Aflatoxin and Fumonisin Detection in Maize.

The aim of this study was to evaluate the potential use of an e-nose in combination with lateral flow immunoassays for rapid aflatoxin and fumonisin occurrence/co-occurrence detection in maize samples. For this purpose, 161 samples of corn have been used. Below the regulatory limits, single-contaminated, and co-contaminated samples were classified according to the detection ranges established for commercial lateral flow immunoassays (LFIAs) for mycotoxin determination. Correspondence between methods was evaluated by discriminant function analysis (DFA) procedures using IBM SPSS Statistics 22. Stepwise variable selection was done to select the e-nose sensors for classifying samples by DFA. The overall leave-out-one cross-validated percentage of samples correctly classified by the eight-variate DFA model for aflatoxin was 81%. The overall leave-out-one cross-validated percentage of samples correctly classified by the seven-variate DFA model for fumonisin was 85%. The overall leave-out-one cross-validated percentage of samples correctly classified by the nine-variate DFA model for the three classes of contamination (below the regulatory limits, single-contaminated, co-contaminated) was 65%. Therefore, even though an exhaustive evaluation will require a larger dataset to perform a validation procedure, an electronic nose (e-nose) seems to be a promising rapid/screening method to detect contamination by aflatoxin, fumonisin, or both in maize kernel stocks.

Development of Spatial Distribution Model using GIS to Identify Social Support Index Among Drug-Abuse Inmates

This study was to identify the spatial distribution of Social Support Index (SSI) among drug-abuse inmates throughout Peninsular Malaysia. Factor Analysis (FA) and Discriminant Analysis (DA) were applied to analyses the level of social support (SS) among drug-abuse inmates and develop the spatial model using Geographic Information System (GIS). Five significant index categories were generated from FA: excellent, good, moderate, low and poor Quality of Life Index (QoLi) and the nine of SS variables are expected to be derived from family, friends and other social factor. DA showed each category differed from others in terms of different compositions, stepwise backward and forward modes gave 99.75% correct classification. GIS analysis show the distribution of SSI categorized on family and friends factor were moderately for where the prisoners came. Besides that, Perlis classified as low-level index and Melaka as high-level index of other social factor. The distribution model of SSI in moderately-level showed Jelebu, Sungai Petani, Pengkalan Chepa and Simpang Renggang as the better SS factor to quality of life compared to the Penor, Pahang. The procedures of FA, DA and GIS were used in this study proved the source apportionment of SS and QoLi among drug-abuse inmates in Peninsular Malaysian prisons.

Assessment of surface water quality in Legedadie and Dire catchments, Central Ethiopia, using multivariate statistical analysis

The quality of surface water in an area could be determined both by anthropogenic actions and natural processes. The current study assessed surface water quality in Legedadie and Dire catchments that cover a total area of 285 km2 in Central Ethiopia northeast of the nation’s capital Addis Ababa and within close proximity (20-30 m) from this city.. Accordingly, Addis Ababa is, and will continue to be, the major beneficiary of the the catchments which are in fact the primary sources of potable water supply to the city. Despite its potential ecosystem benefits, the catchment area was seriously affected by the rapid socioeconomic development phenomena that had been taking place in and around the city over the previous six decades. As a result, the catchment water resources are characterized by decades of deterioration because of severe pollution problems directly associated with mismanagement of natural resources coupled with other several factors. Hence, the current study was sought to examine the temporal and spatial determinants of catchment water pollutants. To that end, 14 water quality monitoring stations were selected and set up both in upstream and downstream parts of six rivers and two reservoirs. The water samples collected from different sites were monitored for 30 standard water quality parameters including nutrients, inorganic variable, and trace metals. Seasonal data were then measured for the 30 parameters monitored across two seasons (summer and autumn) over a two-year period (June 2014 – November 2015). The complex two-year seasonal data matrix that comprised of 3,660 observations was treated using multivariate statistical techniques: cluster analysis (CA), factor analysis/principal components (FA/PCA), and discriminant analysis (DA). CA successfully classified both the temporal (summer, autumn, and summer predominant) and spatial (natural, agricultural, urban, and mixed) clusters of water quality monitoring sites. Dimension reduction from FA/PCA was not as substantial as expected since it enabled only30% reduction from the original data matrix. On the other hand, DA procedures demonstrated the best result regarding data reduction and pattern recognition in both temporal and spatial analysis. It extracted data significantly and provided 5 parameters (Temp, pH, DO, salinity, and TN) to afford 96.8% right allocations during temporal analysis and only 7 parameters (pH, Turbidity, TN, Total hardness, Pb, Fe, and Cu) to yield 85.2% right allocations during the spatial analysis.Thus, these water quality parameters were most significant for seasonal and spatial water quality variation in the catchment. Therefore, DA enabled a significant reduction of the dimension of the original data matrix into a few significant parameters that affect water quality. In conclusion, the study demonstrated that multivariate statistical techniques are very useful for analysis and interpretation of complex water quality data sets for efficient assessment of water quality and identification of pollution sources as well as an effective understanding of the space and time effects of water quality.

Integrative taxonomy at the nexus of population divergence and speciation in insular speckled rattlesnakes

ABSTRACTWe describe two diminutive species of rattlesnakes (genus Crotalus) from small nearshore islands off the coast of Baja California in the western Gulf of California, Mexico. In order to test the hypothesis that some island populations represent cohesive species entities, we applied linear discriminant analysis and uniform validation procedures to multiple classes of intrinsic trait data. By using previously recognised species to establish a threshold for species recognition, we found that assignment of specimens to either new species was as probable as with other established rattlesnake species within the speckled rattlesnake (Crotalus mitchellii) complex. We also found that assignment of specimens from other island populations was not as probable as for the established species, and these populations are referable to C. pyrrhus. The species endemic to Piojo Island is most closely related to other island and mainland populations of C. pyrrhus whereas the species endemic to Cabeza de Caballo Island is apparently most closely related to C. angelensis, a nearby island endemic of large body size. However, patterns from both mitochondrial and nuclear phylogenies, and phenotypic variation, indicate that evolutionary trajectories of both of these species have been influenced by introgression from C. angelensis. We speculate that collective evidence based on contrasting patterns of nuclear and mitochondrial evolution supports a hybrid origin of the species from Cabeza de Caballo Island followed by exceptionally rapid mitochondrial evolution. Consistent with small body size, both species show a reduction in various scale counts relative to other species of the C. mitchellii species complex, suggesting that dwarfism is not simply a plastic response to insular conditions.http://www.zoobank.org/urn.lsid:zoobank.org:pub:FBC8A11B-04A3-4231-85CA-3972DF5A42FF

Моделирование структуры нарушений высших психических функций у больных хроническим алкоголизмом на основе данных нейропсихологического исследования

The article described some problems of the organization and content of the experimental neuropsychological study of patients with alcoholism. We presented a brief analysis of the current state of neuropsychological diagnostics with reference to the problems of quantitative, instrumental and system diagnostics in general clinical practice and especially in the clinic of addictions. We described and analyzed the materials of a clinical-neuropsychological study of a sample including 72 patients with alcoholism, and their secondary processing was performed according to a previously developed algorithm for tabular differential diagnosis of variants of organic personality disorder. In the paper we described the results of discriminant analysis procedures in the groups of patients with alcoholism. The groups were formed according to external clinical criteria. We distinguished a number of prognostically significant experimentally established variables, including impulsivity, uncontrolled emotions, difficulty in formulating (verbalization), memory impairment and depletion of activity. It is shown that the predictive accuracy of the developed discriminant model is 72.2% and allows one to reliably differentiate patients according to the combination of the severity of the disease and the objectivization of the duration of the disease.