Visualizing Correlations Recitation

Week 8

Author

Jessica Cooperstone

Introduction

We will be using some data collection from the National Health and Nutrition Examination Survey which collects data to assess the health and nutritional status of people in the United States. The data from 2009-2012 has been compiled in an R package called NHANES.

# install.packages("NHANES")
library(NHANES)

# functionality and correlation packages
library(tidyverse)
library(corrplot)
library(ggcorrplot)
library(GGally)
library(Hmisc)
library(reshape2)
library(scales)

knitr::kable(head(NHANES))
ID SurveyYr Gender Age AgeDecade AgeMonths Race1 Race3 Education MaritalStatus HHIncome HHIncomeMid Poverty HomeRooms HomeOwn Work Weight Length HeadCirc Height BMI BMICatUnder20yrs BMI_WHO Pulse BPSysAve BPDiaAve BPSys1 BPDia1 BPSys2 BPDia2 BPSys3 BPDia3 Testosterone DirectChol TotChol UrineVol1 UrineFlow1 UrineVol2 UrineFlow2 Diabetes DiabetesAge HealthGen DaysPhysHlthBad DaysMentHlthBad LittleInterest Depressed nPregnancies nBabies Age1stBaby SleepHrsNight SleepTrouble PhysActive PhysActiveDays TVHrsDay CompHrsDay TVHrsDayChild CompHrsDayChild Alcohol12PlusYr AlcoholDay AlcoholYear SmokeNow Smoke100 Smoke100n SmokeAge Marijuana AgeFirstMarij RegularMarij AgeRegMarij HardDrugs SexEver SexAge SexNumPartnLife SexNumPartYear SameSex SexOrientation PregnantNow
51624 2009_10 male 34 30-39 409 White NA High School Married 25000-34999 30000 1.36 6 Own NotWorking 87.4 NA NA 164.7 32.22 NA 30.0_plus 70 113 85 114 88 114 88 112 82 NA 1.29 3.49 352 NA NA NA No NA Good 0 15 Most Several NA NA NA 4 Yes No NA NA NA NA NA Yes NA 0 No Yes Smoker 18 Yes 17 No NA Yes Yes 16 8 1 No Heterosexual NA
51624 2009_10 male 34 30-39 409 White NA High School Married 25000-34999 30000 1.36 6 Own NotWorking 87.4 NA NA 164.7 32.22 NA 30.0_plus 70 113 85 114 88 114 88 112 82 NA 1.29 3.49 352 NA NA NA No NA Good 0 15 Most Several NA NA NA 4 Yes No NA NA NA NA NA Yes NA 0 No Yes Smoker 18 Yes 17 No NA Yes Yes 16 8 1 No Heterosexual NA
51624 2009_10 male 34 30-39 409 White NA High School Married 25000-34999 30000 1.36 6 Own NotWorking 87.4 NA NA 164.7 32.22 NA 30.0_plus 70 113 85 114 88 114 88 112 82 NA 1.29 3.49 352 NA NA NA No NA Good 0 15 Most Several NA NA NA 4 Yes No NA NA NA NA NA Yes NA 0 No Yes Smoker 18 Yes 17 No NA Yes Yes 16 8 1 No Heterosexual NA
51625 2009_10 male 4 0-9 49 Other NA NA NA 20000-24999 22500 1.07 9 Own NA 17.0 NA NA 105.4 15.30 NA 12.0_18.5 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA No NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 4 1 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
51630 2009_10 female 49 40-49 596 White NA Some College LivePartner 35000-44999 40000 1.91 5 Rent NotWorking 86.7 NA NA 168.4 30.57 NA 30.0_plus 86 112 75 118 82 108 74 116 76 NA 1.16 6.70 77 0.094 NA NA No NA Good 0 10 Several Several 2 2 27 8 Yes No NA NA NA NA NA Yes 2 20 Yes Yes Smoker 38 Yes 18 No NA Yes Yes 12 10 1 Yes Heterosexual NA
51638 2009_10 male 9 0-9 115 White NA NA NA 75000-99999 87500 1.84 6 Rent NA 29.8 NA NA 133.1 16.82 NA 12.0_18.5 82 86 47 84 50 84 50 88 44 NA 1.34 4.86 123 1.538 NA NA No NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 5 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

1. How correlated are different measures of blood pressure?

In the NHANES dataset, there are 3 measurements for each systolic (the first/top number) and diastolic blood (the second/bottom number) pressure. How reproducible is each type of blood pressure measurement over the 3 samplings? Make visualizations to convey your findings.

2. How correlated are different physical measurements, health, and lifestyle variables?

In the NHANES dataset, there are data for subject BMI, Pulse, BPSysAve, BPDiaAve, TotalChol.

Create a series of plots/plot to show the relationship between these variables with each other.

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