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Parameters entered into model: Gender, education, economic status, father's job, parental interest in weight, father's body shape, mother's body shape.
Confounding factors tested but did not remain in the final model: gender, education, injury severity Interactions were tested and one interaction (co-morbid health conditions by self employed worker) met the criteria to remain in the model.
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In the unadjusted models, gender, education, religion, working status, history of alcohol use, tobacco use, substance use and camp were all statistically significantly associated with hazardous alcohol consumption.
In the multivariable model, gender, age, education, household type, residence, season, province and travel were significant risk factors of being a case of AGI.
She used antecedents like the personality traits, role model, age, gender, education, and experience to predict the social entrepreneurial intention.
The final model included gender, education, baseline and follow-up CD4 cell count, and baseline GDS.
Relative hazards (RH) of dying were controlled in models including gender, education, medical and mental health, social relations, help given and received, and health behaviour.
The model covariates were gender, education, age at BRSD assessment, baseline MMSE score, duration of illness, and baseline CDR score.
This model included age, gender education and the presence of APOE ϵ4 allele in addition to the studied biomarker.
Further, peak VO2 accounted for roughly 20% of the variance in FA in four of the five regions examined when it was entered into the model after age, gender, education, and depression scores, indicating that peak VO2-FA associations are not simply accounted for by correlations with age, gender, education, or depression.
In addition, potential confounders included in the model were age, gender, education level, employment status, marital status, living situation (alone: no/yes), ethnicity, taking prescription medications (no/yes), co-morbid medical conditions including other eye conditions (no/yes) and wears glasses after surgery (no/yes).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com