Is There An Error Term In Logistic Regression
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Regression - Error Term and its Distribution up vote 12 down vote favorite 6 On whether an error term exists in logistic regression (and its assumed distribution), I have read in various places that: no error term exists the error term has a binomial distribution (in accordance with the distribution of the response variable) the error term has a logistic distribution Can someone please clarify? logistic binomial bernoulli-distribution share|improve this question edited Nov 20 '14 at probit regression 12:43 Frank Harrell 39.1k173156 asked Nov 20 '14 at 10:57 user61124 6314 4 With logistic regression - or indeed GLMs more generally - it's typically not useful to think in terms of the observation $y_i|\mathbf{x}$ as "mean + error". Better to think in terms of the conditional distribution. I wouldn't go so far as to say 'no error term exists' as 'it's just not helpful to think in those terms'. So I wouldn't so much say it's a choice between 1. or 2. as I would say it's generally better to say "none of the above". However, irrespective of the degree to which one might argue for "1." or "2.", though, "3." is definitely wrong. Where did you see that? –Glen_b♦ Nov 20 '14 at 13:52 @Glen_b: Might one argue for (2)? I've known people to say it but never to defend it when it's questioned. –Scortchi♦ Nov 20 '14 at 14:49 2 @Glen_b All three statements have constructive interpretations in which they are true. (3) is addressed at en.wikipedia.org/wiki/Logistic_distribution#Applications and en.wikipedia.org/wiki/Discrete_choice#Binary_Choice. –whuber♦ Nov 20 '14 at 20:11 @whuber: I've corrected my answer wrt (3), which wasn't well thought through; but still puzzled about in what sense (2) might be right. –Scortchi♦ Nov 20 '14 at 21:27 1 @Scortchi Although you are right that (2) is incorrect, if
AnalysisData Analysis PlanIRB / URRQuantitative ResultsQualitative ResultsDiscussion CloseDirectory Of Statistical AnalysesCluster AnalysisConduct and Interpret a Cluster AnalysisCluster Analysis ConsultingGeneralConduct and logistic regression assumptions Interpret a Profile AnalysisConduct and Interpret a Sequential multinomial logistic regression One-Way Discriminant AnalysisMathematical Expectation[ View All ]Regression AnalysisAssumptions of Linear RegressionTwo-Stage Least logistic distribution Squares (2SLS) Regression AnalysisUsing Logistic Regression in Research[ View All ]CorrelationCorrelation (Pearson, Kendall, Spearman)Correlation RatioMeasures of Association[ View All http://stats.stackexchange.com/questions/124818/logistic-regression-error-term-and-its-distribution ](M)ANOVA AnalysisAssumptions of the Factorial ANOVAGLM Repeated MeasureGeneralized Linear Models[ View All ]Factor Analysis & SEMConduct and Interpret a Factor AnalysisExploratory Factor AnalysisConfirmatory Factor Analysis[ View All ]Non-Parametric AnalysisCHAIDWald Wolfowitz Run Test[ View All ] CloseDirectory Of Survey InstrumentsAttitudesEmotional http://www.statisticssolutions.com/assumptions-of-logistic-regression/ IntelligenceLearning / Teaching / SchoolPsychological / PersonalityWomenCareerHealthMilitarySelf EsteemChildLeadershipOrganizational / Social GroupsStress / Anxiety / Depression Close CloseFree ResourcesNext Steps Home | Academic Solutions | Directory of Statistical Analyses | Regression Analysis | Assumptions of Logistic Regression Assumptions of Logistic Regression Logistic regression does not make many of the key assumptions of linear regression and general linear models that are based on ordinary least squares algorithms – particularly regarding linearity, normality, homoscedasticity, and measurement level. Click Here to Start Using Intellectus Statistics for Free Firstly, it does not need a linear relationship between the dependent and independent variables. Logistic regression can handle all sorts of relationships, because it applies a non-linear log transformation to the predicted odds
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