Sentence examples for multivariable model data from inspiring English sources

Furthermore, TAP was independent of PR when assessed as a multivariable model (data not shown).> In an exploratory multivariate analysis of TAP status and common clinical variables, TAP was independent of age, stage, hormonal therapy and chemotherapy status with 5 year recurrence as the outcome measurement in all patients (Table  3).

Individuals with a previous hospital record of psychosis had no increased risk for current use of other antipsychotics in the crude or full multivariable model (data not shown).

The univariable analysis confirmed that the variables in the original BALAD model are all highly prognostic (Table 3), and these factors maintained statistical significance in the resulting multivariable model (data not shown).

Similarly, stratifying separately by the presence of HLA-DRB1 SE and anti-CCP antibodies, the AA and AG genotypes of rs1801275 were associated with rheumatoid nodules (ORadj = 8.12 (95% CI, 1.59 to 41.44), P = 0.01; and ORadj = 2.96 (95% CI, 1.15 to 7.62), P = 0.02; respectively) in the multivariable model (data not shown).

Similar results were obtained, if ever smoking (current/never/exsmoking) or pack-years were used as covariates in multivariable models (data not shown).

Our results were also unchanged in sensitivity analyses of NHANES 2005 2006, the only years for which OGTT data were available, in which we further excluded individuals with impaired glucose tolerance (2-h glucose ≥140 mg/dl) from our multivariable models (data not shown).

These results were consistent across sensitivity analyses adjusted for age, tumor stage, pre-diagnostic PA level, and time from breast cancer diagnosis to post-diagnostic PA assessment; and also when use of hormone therapy, BMI, and smoking were added to the multivariable models (data not shown).

The multivariable model included data on 1705 women due to missing data on correlates.

Sensitivity analysis with 90-day chemotherapy delay threshold yielded similar results in the multivariable regression model (data not shown) with year of diagnosis (OR = 1.37, p < 0.001), re-excision (OR = 3.96, p = 0.001) and public hospital care (OR = 4.89, p = 0.001) showing significant associations.

The goodness-of-fit of the final multivariable model to the data, as assessed by the Hosmer-Lemeshow goodness of fit test, was adequate (P = 0.816).

When IDUs were excluded, the multivariable model predicted the data less well (–2 log likelihood with IDUs = –686.7, without = –660.2), but this exclusion affected neither the direction of the ORs nor their size in a relevant way (data not shown).