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Stata software version 14.2 for windows

Manufactured by StataCorp
Sourced in United States

Stata is a general-purpose statistical software package developed by StataCorp. Version 14.2 is the latest release for the Windows operating system. Stata provides a comprehensive set of tools for data management, statistical analysis, and visualization. It is widely used in various fields, including economics, social sciences, and medical research.

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Lab products found in correlation

2 protocols using stata software version 14.2 for windows

1

Sensitivity Analysis of HBV Vaccination

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Two sensitivity analyses were conducted to assess the robustness of the results when considering two alternative outcomes, which were defined by changing the criteria for timeliness. For the first outcome, we separately assessed non-adherence to the BD and to the three-dose schedules, using a less restrictive timeliness threshold of seven days after birth (instead of 24 h) for the BD. For the second outcome, we assessed non-adherence to the overall HBV vaccination schedule as set out in Senegal’s EPI. More specifically, the EPI provides for a total of four doses (i.e., the BD and three pentavalent doses), with a minimum of four weeks between the second and third pentavalent dose (WHO and national recommendations [9 (link),20 ]).
All statistical analyses were performed using Stata software, version 14.2 for Windows (StataCorp, College Station, TX, USA).
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2

Plasmodium Infection Prevalence Factors

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Data were collected and managed using REDCap electronic data capture tools [18 (link), 19 (link)] hosted at New York University and analysed using Stata software, version 14.2 for Windows (StataCorp, College Station, Texas). Data analyses were conducted using a complete-case approach, whereby participants with missing data for relevant variables were excluded. Summary statistics for continuous variables are presented as mean and standard deviation (SD) or median and interquartile range (IQR, 25th–75th percentile), depending on the distribution of data and as numbers and percentages (%) for categorical variables. The prevalence of Plasmodium infection, along with the 95% confidence interval (CI), was calculated using the Taylor linearized method that accounts for the clustered data-structure [20 ]. Associations between household and individual level socio-demographic, environmental and behavioural risk factors, and Plasmodium infections were evaluated using multilevel logistic regression models with exchangeable correlation matrix, considering village and household as grouping variables and reported as odds ratios (OR) with 95% CIs.
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