Publications by Dr Samuel Blay Nguah
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Charles’ Sample Size The sample size for the study was based on the following: Since there is no prior study comparing neurocognitive function among adolescents with HIV, the study was powered to determine the difference in prevalence of factors associated with neurocognitive study of 25%. We used the assumption that the prevalence of risk facto...
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Table of contents Reading in the data Data modification Filling in missing values Generating terciles per study site Labelling variables Creating functions for regression Table 1 Table 2 Creating Table 2 Exporting Table 2 Figure I Creating different figures Combining figures into one Exporting Figure Table 3 Table 4 Table 5 Table 6 Drawing ta...
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Table of contents Data Management Table I: Summary of the complete dataset Table 1 Table 2 Table 3 table 4 Table 5 Table 6 Table 7 Table 8 Table 9 Table 10 Felicia Part II Analysis Author Dr Samuel Blay Nguah Published September 16, 2023 Data Management Table I: Summary of the complete dataset Code df_complete %>% summarytools::dfSummary(...
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Paper4
Table of contents Data summary Table 1 Table 3 Paper 4 Author Dr Samuel Blay Nguah Published September 16, 2023 Note General comments Please note the summary below for the number of missing variables and data from the database Table 1 Perceived Stress: You will have to indicate how you intend to derive this variable Primary Occupation:...
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Paper 5
Data summary df_paper05 <- dget("pings2_data_clean") %>% #labelled::lookfor("stroke") filter(eventname == "Baseline") %>% select( pid, eventname, datagrp, partid, sid, arm, starts_with("a_"), ff_hba1c_0, ee_sbp_0, ee_dbp_0, ee_bmi_0, ee_waistc_0, g_tabacco,ff_totchol_0, ff_ldl_0, ff_hdl_0, ff_trigly_0,...
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Data Management df_ascvd <- readxl::read_excel( path = "Procat-Gh Data_Added 1.xlsx", sheet = "ASCVD Data 2 New" ) %>% janitor::clean_names() #------------------------------------------------------------------------------- df_ascvd <- df_ascvd %>% mutate( sex = factor(sex, levels = c("F"...
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Read in and summarize data df_cimt <- readxl::read_xlsx("SMAART manuscript_Interrater assessment.xlsx") %>% na.omit() df_cimt %>% summarytools::dfSummary(graph.col = F) Data Frame Summary df_cimt Dimensions: 292 x 3 Duplicates: 167 ------------------------------------------------------------------------------------ No V...
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Data comments for the analysis ofc is missing 11 observations length is missing 11 observations Maternal income has 68 missing values Maternal blood group has 8 missing maternal rhesus has 8n missing Fathers age has 9 missing observations Fathers income has 156 missing Fathers blood group has 174 missing No outcome for one patient One patient with...
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Sample size determination To determine the proportion of children with nephrotic syndrome with hypovolemia, the sample size for the study was determined using the proportion of children with nephrotic syndrome and hypovolemia of 25%, as reported by XXX et. al., in Turkey. Using a precision of 12.5% from the estimate, and a 95% confidence limit,...
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Reading in the data df_phd <- haven::read_sav( "20221209_RODAMbaseline_ProsRODAMfollowup_Dec2022_Lambert.sav" ) %>% droplevels() %>% rename( R1_Factor3rootstuber = R1_Factor3rootstubersandplantainpattern, R1_vegetable_soups_st = R1_vegetable_soups_stews_sauces ) %>% labelled::unlabelled()...
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