Test for model specification error.
blr_linktest(model)
model | An object of class |
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An object of class glm
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Pregibon, D. 1979. Data analytic methods for generalized linear models. PhD diss., University of Toronto.
Pregibon, D. 1980. Goodness of link tests for generalized linear models.
Tukey, J. W. 1949. One degree of freedom for non-additivity.
model <- glm(honcomp ~ female + read + science, data = hsb2, family = binomial(link = 'logit')) blr_linktest(model) #> #> Call: #> glm(formula = resp ~ fit + fit2, family = binomial(link = "logit"), #> data = newdat) #> #> Deviance Residuals: #> Min 1Q Median 3Q Max #> -1.8578 -0.6168 -0.2987 0.5102 2.6096 #> #> Coefficients: #> Estimate Std. Error z value Pr(>|z|) #> (Intercept) 0.03569 0.23399 0.153 0.879 #> fit 0.93715 0.20767 4.513 6.4e-06 *** #> fit2 -0.03920 0.08970 -0.437 0.662 #> --- #> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 #> #> (Dispersion parameter for binomial family taken to be 1) #> #> Null deviance: 231.29 on 199 degrees of freedom #> Residual deviance: 160.04 on 197 degrees of freedom #> AIC: 166.04 #> #> Number of Fisher Scoring iterations: 6 #>