Both univariate and multivariable methods were used to identify factors associated with receipt of guideline care for initial therapy for those with nonmetastatic. The χ2 tests were used to determine univariate differences and multivariable logistic regression modeling was used to estimate significant independent predictors of use of guideline-discordant care, including variables that were significant at P < 0.10 from the univariate results. The results of the logistic regression analyses were expressed as adjusted odds ratios (ORs) with 95% confident limits (CL). All results were weighted based on the sampling fraction to provide results that represented the source population of the sampled cases using SAS Proc Survey-Logistic and SAS Proc SurveyFreq.
Sas proc surveyfreq
Manufactured by SAS Institute
SAS PROC SURVEYFREQ is a statistical procedure within the SAS software suite that provides analysis of frequency tables for survey data. It calculates statistical estimates and associated standard errors for various frequency measures, including totals, percentages, and confidence limits. The procedure handles the complexities of survey sample designs, such as stratification, clustering, and unequal weighting.
Automatically generated - may contain errors
Lab products found in correlation
5 protocols using sas proc surveyfreq
1
Identifying Factors of Guideline-Discordant Care
2
Analyzing Factors Affecting Vital Status in Discharge
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
We excluded records from analysis if they were missing vital status at discharge, DM status, age, or sex. Weighted continuous variables are summarized as mean±SE, and weighted categorical variables are summarized as counts or percentages ±SE. For analysis purposes, age was categorized as <55, 55 to 64, 65 to 74, 75 to 84, and ≥85 years, with the “<55 years” category serving as the reference group. We used survey regression procedures designed to incorporate NIS‐specified weights for descriptive statistics and multivariable models. Trends in categorical variables were tested using the Wald chi‐square statistics (SAS PROC SURVEYFREQ; SAS Institute Inc.).
3
Sociodemographic Factors Influencing HIV Status
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
SAS 9.4 was used for all statistical analyses. SAS PROC SURVEYFREQ was used to produce frequencies adjusting for clustering of observations within communities. Bivariate tests of association were conducted using Rao-Scott Chi-square tests, with a critical alpha level of 0.05. SAS PROC SURVEYLOGISTIC was used to test for association between sociodemographic factors of interest and HIV positivity, prior knowledge of HIV-positive status and ART status. These models produced unadjusted and adjusted odds ratios (ORs) and 95% confidence limits.
4
Sociodemographic Factors and HIV Prevalence
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
SAS 9.4 was used for all statistical analyses. SAS PROC SURVEYFREQ was used to produce frequencies, adjusting for clustering of observations within communities. Bivariate tests of association were conducted using Rao-Scott Chi-square tests, with a critical alpha level of 0.05. SAS PROC SURVEYLOGISTIC was used to test for association between sociodemographic factors of interest and HIV positivity. These models produced unadjusted and adjusted odds ratios (ORs) and 95% confidence limits.
5
Prevalence and Patterns of Binge Drinking
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
We first calculated descriptive statistics to estimate the weighted prevalence of binge drinking, overall and by each category of covariate. The SAS PROC SURVEYFREQ was used for weighted estimation of prevalence and Chi-square test was used to compare the prevalence of binge drinking across demographic subgroups (age, gender, and race), socioeconomic factors (income level, health condition, and health insurance status), clinical factors (multiple chronic disease and SPD), and substance use associated factors (SUD, early onset of alcohol use, early onset of smokeless tobacco use, and early onset of marijuana use). We also calculated the weighted mean number of days of binge drinking in the past month across the subgroups through SAS PROC SURVEYMEANS.
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!