MARC Record from marc_columbia

LEADER: 03092mam a2200349 a 4500
001 3142069
005 20221019232217.0
008 010402t20022002caua b 000 0 eng
010 $a 2001019806
020 $a0761922083 (acid-free paper)
035 $a(OCoLC)ocm46729126
035 $9ATX8236CU
035 $a(NNC)3142069
035 $a3142069
040 $aDLC$cDLC$dOrLoB-B
050 00 $aQA278.2$b.M46 2002
082 00 $a519.5/36$221
100 1 $aMenard, Scott W.$0http://id.loc.gov/authorities/names/n85320093
245 10 $aApplied logistic regression analysis /$cScott Menard.
250 $a2nd ed.
260 $aThousand Oaks, Calif. :$bSage Publications,$c[2002], ©2002.
300 $aviii, 111 pages :$billustrations ;$c22 cm.
336 $atext$btxt$2rdacontent
337 $aunmediated$bn$2rdamedia
490 1 $aSage university papers. Quantitative applications in the social sciences ;$vno. 07-106
504 $aIncludes bibliographical references (p. 108-110).
505 00 $g1.$tLinear Regression and the Logistic Regression Model.$g1.1.$tRegression Assumptions.$g1.2.$tNonlinear Relationships and Variable Transformations.$g1.3.$tProbabilities, Odds, Odds Ratios, and the Logit Transformation for Dichotomous Dependent Variables.$g1.4.$tLogistic Regression: A First Look --$g2.$tSummary Statistics for Evaluating the Logistic Regression Model.$g2.1.$tR[superscript 2], F, and Sums of Squared Errors.$g2.2.$tGoodness of Fit: G[subscript M], R[subscript L][superscript 2], and the Log Likelihood.$g2.3.$tPredictive Efficiency: [lambda][subscript p], [tau][subscript p], [phi][subscript p], and the Binomial Test.$g2.4.$tExamples: Assessing the Adequacy of Logistic Regression Models.$g2.5.$tConclusion: Summary Measures for Evaluating the Logistic Regression Model --$g3.$tInterpreting the Logistic Regression Coefficients.$g3.1.$tStatistical Significance in Logistic Regression Analysis.$g3.2.$tInterpreting Unstandardized Logistic Regression Coefficients.
505 80 $g3.3.$tSubstantive Significance and Standardized Coefficients.$g3.4.$tExponentiated Coefficients or Odds Ratios.$g3.5.$tMore on Categorical Predictors: Contrasts and Interpretation.$g3.6.$tInteraction Effects.$g3.7.$tStepwise Logistic Regression --$g4.$tAn Introduction to Logistic Regression Diagnostics.$g4.1.$tSpecification Error.$g4.2.$tCollinearity.$g4.3.$tNumerical Problems: Zero Cells and Complete Separation.$g4.4.$tAnalysis of Residuals.$g4.5.$tOverdispersion and Underdispersion.$g4.6.$tA Suggested Protocol for Logistic Regression Diagnostics --$g5.$tPolytomous Logistic Regression and Alternatives to Logistic Regression.$g5.1.$tPolytomous Nominal Dependent Variables.$g5.2.$tPolytomous or Multinomial Ordinal Dependent Variables.$g5.3.$tConclusion.
650 0 $aRegression analysis.$0http://id.loc.gov/authorities/subjects/sh85112392
650 0 $aLogistic distribution.$0http://id.loc.gov/authorities/subjects/sh91004798
830 0 $aQuantitative applications in the social sciences ;$vno. 07-106.$0http://id.loc.gov/authorities/names/n42021487
852 00 $bleh$hQA278.2$i.M46 2002