A frequency distribution table was prepared for all the variables used in this study. Prevalence of malaria with each of the SES (age group, sex, residence area, education level, MPCE quintiles, caste, and work) and household variables (household size, type of house, location of water source, toilet type, cooking fuel, and damp wall or ceiling) were reported. Simple logistic regression was used to obtain the unadjusted odds ratio (UOR), and those independent variables found significant (P < 0.05) were included in the multiple logistic regression to arrive at the Adjusted Odds Ratio (AOR) of SES and household variables in association with malaria. All the independent variables were significant at the alpha value of 5 % except for the variable ‘sex’ in the univariable logistic regression analysis. The variable ‘sex’ was used in the multivariable logistic regression despite not found significant in the univariable analysis because ‘sex’ is an important variable to adjust for in the analysis. Sampling weights calculated by LASI were applied during the analysis to obtain accurate estimates. All analyses were performed using STATA MP statistical software version 16.
Stata mp statistical software version 16
Manufactured by StataCorp
Sourced in United States
STATA MP is a statistical software package developed by StataCorp. Version 16 provides advanced data analysis and statistical modeling capabilities. The software is designed to handle large datasets and complex statistical computations.
Automatically generated - may contain errors
Lab products found in correlation
2 protocols using stata mp statistical software version 16
1
Socioeconomic Factors and Malaria Prevalence
2
Cardiovascular Disease Prevalence Analysis
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
A frequency and percentage distribution table were constructed for all the study variables according to men, women, and the total sample. The prevalence of CVDs was stratified across sociodemographic and lifestyle factors. We used Pearson chi-squared test to test for statistically significant differences in CVDs prevalence between groups. The adjusted odds ratios (aOR) were estimated by employing the multivariable logistic regression model with the following variables in the model: age group, sex, rural/urban, education, MPCE quintile, caste, state-region, hypertension, high cholesterol, diabetes, physical inactivity, BMI, sleep, family history of CVDs, smoke and alcohol use. We have presented the aORs and their corresponding 95% Confidence Intervals (CIs) graphically for men, women and the total sample. Survey weights provided in the dataset were applied during the data analysis to obtain accurate estimates. The level of statistical significance was set at p < 0.05, and two-tailed test values were presented. We used the Stata MP statistical software version 16 (StataCorp, TX, USA) for all statistical analyses.
About PubCompare
Our mission is to provide scientists with the largest repository of trustworthy protocols and intelligent analytical tools, thereby offering them extensive information to design robust protocols aimed at minimizing the risk of failures.
We believe that the most crucial aspect is to grant scientists access to a wide range of reliable sources and new useful tools that surpass human capabilities.
However, we trust in allowing scientists to determine how to construct their own protocols based on this information, as they are the experts in their field.
Ready to get started?
Sign up for free.
Registration takes 20 seconds.
Available from any computer
No download required
Revolutionizing how scientists
search and build protocols!