*2.6. Statistical Analysis*

The data collected during the interview, information about the vaccines recorded on the vaccination card, and the vaccine data obtained from the *SI-PNI* were exported to statistical analysis software (IBM SPSS®, version 24 and StataCorp. 2021. Stata Statistical Software: Release 17. College Station, TX, USA: StataCorp LLC.).

All analyses were performed using the complex sample design. Stata's "survey" package was used. The selected families were included as PSU, and the type of community (settlement/quilombola communities) was used as a stratum. Individual selection sample weights were included for each child [23], considering the selection probability according to their community, sex, and age group.

A descriptive analysis of the participants' characteristics was carried out initially, followed by Pearson's chi-square test corrected for design to assess differences in characteristics between children from settlements and communities. Estimates of the coverage of the complete immunization schedule by type of vaccine and type of community were then calculated, along with 95% Confidence Intervals (95%CI). Next, bivariate and multiple analyses were performed using binary logistic regression to identify the factors associated with incomplete general vaccination coverage. In the bivariate analysis, the dependent variable was associated with each of the independent variables analyzed. Next, the variables that presented a *p*-value < 0.25 were included in the multiple logistic regression model, single input method. The magnitude of the multiple analysis effect was presented as Adjusted Odds Ratios (AOR) and 95%CI. Variables with *p*-values < 0.05 were considered significantly associated with the outcome.
