Publications by Joseph Jaiyeola
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Use the same area to search within. Generate an image of your map with a legend for both the WIC and grocery store layers. Report the geocoding results in terms of % correctly geocoded. Use the Census bureau’s geocoding service. Libraries library(mapview) library(sf) ## Linking to GEOS 3.8.1, GDAL 3.2.1, PROJ 7.2.1; sf_use_s2() is TRUE library...
493 sym R (5653 sym/37 pcs)
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#1. Define a binary outcome of your choosing self rated health status 1 Define an ordinal or multinomial outcome variable of your choosing and define how you will recode the original variable. Answer: Health status, with 5 being the worst and 1 being the best health 1&2= 1 (Excellent/V. good) 3=2 (Good) 4&5= 3(Fair/poor) data$generalhealth<-Reco...
17890 sym R (1718 sym/7 pcs) 1 tbl
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#1. Define a binary outcome of your choosing self rated health status 2) Fit a predictive logistic regression model using as many predictor variables as you think you need data$age2<- data$age^2 library(dplyr) model.data<- data %>% select(serial, badhealth, opportunity_youth_cat, urban_rural, male, educ, age2) knitr::kable(head(model.data)) s...
23200 sym R (11254 sym/44 pcs) 4 img 1 tbl
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1. Define a binary outcome variable of your choosing and define how you recode the original variable. Proposed topic: Advserse health conditions associated with opportunity youths Outcome variabels: Health conditions such Health status, depression, anxiety, smoking etc. The purpose of this assignment I would focus on self rated health status 2 S...
23820 sym R (7173 sym/22 pcs) 5 img 3 tbl
GIS-Assignment4
library(tidycensus) library(tidyverse) ## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ── ## ✓ ggplot2 3.3.5 ✓ purrr 0.3.4 ## ✓ tibble 3.1.6 ✓ dplyr 1.0.7 ## ✓ tidyr 1.2.0 ✓ stringr 1.4.0 ## ✓ rea...
790 sym R (16797 sym/44 pcs) 5 img
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temp <- tempfile() #Download the SAS dataset as a ZIP compressed archive download.file("https://data.hrsa.gov/DataDownload/AHRF/AHRF_2019-2020_SAS.zip", temp) #Read SAS data into R ahrf<-haven::read_sas(unz(temp, filename = "ahrf2020.sas7bdat")) rm(temp) #1) Define a count outcome for the dataset of your choosing, the...
10908 sym R (9352 sym/27 pcs) 2 img 4 tbl
Spline
library(ipumsr) setwd("~/Downloads") ddi <- read_ipums_ddi("nhis_00004.xml") data <- read_ipums_micro(ddi) ## Use of data from IPUMS NHIS is subject to conditions including that users ## should cite the data appropriately. Use command `ipums_conditions()` for more ## details. data<- haven::zap_labels(data) names(data) <- tolower(gsub(pattern = "_...
8155 sym R (4990 sym/20 pcs) 4 img
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setwd("~/Downloads") library(ipumsr) ddi <- read_ipums_ddi("usa_00008.xml") data <- read_ipums_micro(ddi) ## Use of data from IPUMS USA is subject to conditions including that users should ## cite the data appropriately. Use command `ipums_conditions()` for more details. data<-haven::zap_labels(data) #necessary to avoid problems with "labelled" d...
43 sym R (2893 sym/19 pcs) 1 img