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Table 3 depicts the mean change OIDP scores by change scores in the categorical reference variables.
Likewise, tooth loss was the strongest covariate of improvement in OIDP after adjusting for country- and other categorical reference variables.
Longitudinal validity was calculated by evaluating the association between OIDP change scores and categorical reference variables using One-Way ANOVA and Bonferroni post hoc test.
GLM repeated measures revealed statistically significant interactions between OIDP scores and change scores of categorical reference variables in both countries (Table 4).
All categorical reference variables contributed to the improvement and worsened of OIDP across the two countries, with change in tooth loss being the strongest covariate.
General Linear Models (GLM) for repeated measures were used to assess the within individual change of OIDP ADD scores by categorical reference variables.
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After all precursor data were transformed into categorical references and values of exposure were calculated, log-linear analysis (Step 6) was performed using SPSS Version 13.0 [16] to calibrate the crash prediction model.
† Residential status is a categorical variable: reference category = Community.
For categorical variables reference categories were chosen according to expected unfavourable prognosis.
Then, if sufficient studies were available, we explored the possible influence of the following pre-specified categorical covariates: reference standard (culture, genetic sequencing, culture and genetic sequencing, culture followed by genetic sequencing) and individual drug (amikacin, kanamycin and capreomycin).
ref = Categorical of reference Patients with at least one vertebral fracture had higher ECOS-16 scores in three domains (Table 5): Physical functioning (p = 0,002); Fear of illness (p = 0,001); Psychosocial functioning (p = 0,007), and in the two summary scores of ECOS-16: PCS (p = 0,01); MCS (p = 0,001).
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CEO of Professional Science Editing for Scientists @ prosciediting.com