Additional file 2: of Explainable statistical learning in public health for policy development: the case of real-world suicide data

Paul Van Schaik (Contributor)
Yonghong Peng (Contributor)
Adedokun Ojelabi (Contributor)
Jonathan Ling (Creator)

Teesside University
SSSHL Psychology

Dataset

Description

Assessing bias. Figure S1. Plot of standardised predicted values against standardised residuals. Figure S2. Histogram and P-P plot of standardised residuals. (ZIP 91 kb)

Date made available	2019
Publisher	figshare

DOI
10.6084/m9.figshare.8948036.v1

Access Dataset

Creative Commons Attribution 4.0 International

1 Article

Explainable statistical learning in public health for policy development: the case of real-world suicide data
Van Schaik, P., Peng, Y., Ojelabi, A. & Ling, J., 17 Jul 2019, In: BMC Medical Research Methodology. 19, 1, 152.
Research output: Contribution to journal › Article › peer-review

Open Access
File
100 Downloads (Pure)

Additional file 2: of Explainable statistical learning in public health for policy development: the case of real-world suicide data

Description

DOI

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Research output

Explainable statistical learning in public health for policy development: the case of real-world suicide data

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