Sensitivity analysis for weighted multinomial logistic regression of primary reason for not participating in DSME on socio-demographic and disease-related characteristics, beliefs and information about diabetes (n = 1396; multiple imputation by chain

<p>* The proportion of missing information per variable ranged from 0% to 5.7%. For 13.5% of respondents, at least one value was imputed. <u>Abbreviations</u>: DMP–Disease-Management-Programme; DSME–structured diabetes self-management education, RRR–Relative risk ratio.</p> <p>(DOCX)</p>

Publication Details

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Figshare
Published
2024-09-12
DOI
https://doi.org/10.1371/journal.pone.0310338.s007
Primary Topic
Statistical Methods in Epidemiology
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article
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Sensitivity analysis for weighted multinomial logistic regression of primary reason for not participating in DSME on socio-demographic and disease-related characteristics, beliefs and information about diabetes (n = 1396; multiple imputation by chain

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Statistical Methods in Epidemiology
article

Sensitivity analysis for weighted multinomial logistic regression of primary reason for not participating in DSME on socio-demographic and disease-related characteristics, beliefs and information about diabetes (n = 1396; multiple imputation by chain

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Abstract

<p>* The proportion of missing information per variable ranged from 0% to 5.7%. For 13.5% of respondents, at least one value was imputed. <u>Abbreviations</u>: DMP–Disease-Management-Programme; DSME–structured diabetes self-management education, RRR–Relative risk ratio.</p> <p>(DOCX)</p>

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Sensitivity analysis for weighted multinomial logistic regression of primary reason for not participating in DSME on socio-demographic and disease-related characteristics, beliefs and information about diabetes (n = 1396; multiple imputation by chain · Figshare (2024) | TGRS Research Map | TGRS