Summary of the steps in constructing the multinomial regression model using the backward elimination method.

aThe χ2 for removal is based on the likelihood ratio test.bBecause each proband’s proportions of older brothers, older sisters, younger brothers, and younger sisters is necessarily summed to 1.00, these proportions were perfectly multicollinear. To reduce the multicollinearity, the computational algorithm of the SPSS multinomial logistic regression program eliminated the proportion of younger brothers from the set of predictor variables.

Tags
Data and Resources
To access the resources you must log in

This item has no data

Identity

Description: The Identity category includes attributes that support the identification of the resource.

Field Value
PID https://www.doi.org/10.1371/journal.pone.0090257.t004
URL http://dx.doi.org/10.1371/journal.pone.0090257.t004
URL https://figshare.com/articles/_Summary_of_the_steps_in_constructing_the_multinomial_regression_model_using_the_backward_elimination_method_/969307
Access Modality

Description: The Access Modality category includes attributes that report the modality of exploitation of the resource.

Field Value
Access Right Open Access
Attribution

Description: Authorships and contributors

Field Value
Author P. VanderLaan, Doug
Author Blanchard, Ray
Author Wood, Hayley
Author J. Zucker, Kenneth
Publishing

Description: Attributes about the publishing venue (e.g. journal) and deposit location (e.g. repository)

Field Value
Collected From figshare
Hosted By figshare
Publication Date 2015-01-01
Publisher Figshare
Additional Info
Field Value
Language UNKNOWN
Resource Type Dataset
keyword mesheuropmc.congenital, hereditary, and neonatal diseases and abnormalities
system:type dataset
Management Info
Field Value
Source https://science-innovation-policy.openaire.eu/search/dataset?datasetId=r37980778c78::f72a1837b7d6459d1bab5b6a4882bafd
Author jsonws_user
Last Updated 3 January 2021, 12:59 (CET)
Created 3 January 2021, 12:59 (CET)