Sentence examples for binary logit regression was from inspiring English sources

Binary logit regression was used to fit the data of codon usage bias (SCUO values as independent variables) of orthologous genes with the presence or absence of intron sequences in the genes (as dependent variables) among the three mosquito species.

To further confirm the negative relationship of codon bias with intron content, binary logit regression was performed to fit the codon usage bias data with the distribution (presence or absence) of intron sequences of the orthologous genes among the three mosquito species.

Because near-complete follow-up characterizes modern databases, binary logit regression is an attractive alternative to Cox regression when PHs violations are deemed important.

Because era, age, tumor size, surgery, and radiotherapy all showed PHs assumption violations with P < 0.0001 by Therneau Grambsch tests, binary logit regressions were applied to calculate odds ratios (OR) at 6 and 12 months after diagnosis.

Binary logit regression model was used to analyze factors affecting local people's knowledge on the adverse impacts of Eucalyptus woodlot.

The result of logit regression is shown in Table 6.

In order to approve this supposition, a multinominal logit regression is conducted on the survey data.

To accurately assess era differences, a reasonable approach lay in binary logit regression, which calculated OR; this was so in part because only 174 (0.8%) of the 20,879 patients were lost to follow-up at 1 year.

Multivariate analysis was performed using binary logit regression software, SAS version 9.0 (Cary, NC 27513 USA).

Table 5 shows the results of the binary logit regression model.

These include a binary logit regression to identify zero outcomes associated with count data and NBR to model the count process.