Comparison of logistic regression and linear discriminant analysis: a simulation study

01/2004; 1:143-161.

ABSTRACT Two of the most widely used statistical methods for analyzing categorical outcome variables are linear discriminant analysis and logistic regression. While both are appropriate for the development of linear classification models, linear discriminant analysis makes more assumptions about the underlying data. Hence, it is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions. In this paper we consider the problem of choosing between the two methods, and set some guidelines for proper choice. The comparison between the methods is based on several measures of predictive accuracy. The performance of the methods is studied by simulations. We start with an example where all the assumptions of the linear discriminant analysis are satisfied and observe the impact of changes regarding the sample size, covariance matrix, Mahalanobis distance and direction of distance between group means. Next, we compare the robustness of the methods towards categorisation and non-normality of explanatory variables in a closely controlled way. We show that the results of LDA and LR are close whenever the normality assumptions are not too badly violated, and set some guidelines for recognizing these situations. We discuss the inappropriateness of LDA in all other cases.

  • Source
  • [Show abstract] [Hide abstract]
    ABSTRACT: A sample of 249 skeletons (154 males, 95 females) from the Chiang Mai University Skeletal Collection was studied to investigate the potential of proximal hand phalanges as indicators of sex among individuals from the Chiang Mai province of Thailand. The sample ranged in age from 19 to 93 years. Six measurements were taken on each proximal phalanx: maximum length, medio-lateral base width, antero-posterior base height, medio-lateral head width, antero-posterior head height and maximum mid-shaft diameter. The measurements were then subjected to ROC analysis as well as binary logistic regression to assess the relative correct allocation accuracy for each bone, and for different combinations of measurements from each bone. All proximal phalanges from both sides exhibited greater than 87% correct allocation accuracy for at least one logistic regression equation that included only two or three measurements. When the sample was limited to individuals with no missing measurements (n=209) in any of the phalanges, the most accurate equations for each proximal phalanx ranged from 87.6% to 92.3%, with the most accurate equation based on two measurements from the left 1st proximal phalanx, and the next most accurate from three measurements of the left 2nd proximal phalanx. The results suggest that proximal phalanges produce better allocation accuracies than metacarpals among modern individuals from Thailand.
    Forensic science international 02/2013; · 2.10 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Methods for identifying dyslexia in adults vary widely between studies. Researchers have to decide how many tests to use, which tests are considered to be the most reliable, and how to determine cut-off scores. The aim of this study was to develop an objective and powerful method for diagnosing dyslexia. We took various methodological measures, most of which are new compared to previous methods. We used a large sample of Dutch first-year psychology students, we considered several options for exclusion and inclusion criteria, we collected as many cognitive tests as possible, we used six independent sources of biographical information for a criterion of dyslexia, we compared the predictive power of discriminant analyses and logistic regression analyses, we used both sum scores and item scores as predictor variables, we used self-report questions as predictor variables, and we retested the reliability of predictions with repeated prediction analyses using an adjusted criterion. We were able to identify 74 dyslexic and 369 non-dyslexic students. For 37 students, various predictions were too inconsistent for a final classification. The most reliable predictions were acquired with item scores and self-report questions. The main conclusion is that it is possible to identify dyslexia with a high reliability, although the exact nature of dyslexia is still unknown. We therefore believe that this study yielded valuable information for future methods of identifying dyslexia in Dutch as well as in other languages, and that this would be beneficial for comparing studies across countries.
    Annals of Dyslexia 12/2013; · 1.48 Impact Factor

Full-text (2 Sources)

Available from
Jul 16, 2014