Data606 Project Proposal
JM
March 28, 2017
Data Preparation
library(psych)
library(ggplot2)
AllAbuseData <- read.csv(file="C:/MSDA/D607/Project2/DrugFatalitiesCT/Accidental_Drug_Related_Deaths__2012-2016.csv")Research question
Two questions - 1) Are people of age less than 40 more likely than those above 40 to be a drug abuse fatality? 2) Are people who live in rural areas more likely than those in urban areas to be a drug abuse fatality?
Cases
What are the cases, and how many are there?
Each case represents a drug abuse fatality in the state of Connecticut during the period of 2012-2015. There 3045 observations in the given data set.
Data collection
Describe the method of data collection.
Data are derived from an investigation by the Office of the Chief Medical Examiner which includes the toxicity report, death certificate, as well as a scene investigation.
Type of study
What type of study is this (observational/experiment)?
This is an observational study.
Data Source
If you collected the data, state self-collected. If not, provide a citation/link.
The site for the drug death data is https://catalog.data.gov/dataset/accidental-drug-related-deaths-january-2012-sept-2015. For the categorization of towns or cities as rural, the data is taken from http://www.ruralhealthct.org/towns.htm, which is maintained by CT Office of Rural Health.
Response
What is the response variable, and what type is it (numerical/categorical)?
There are 2 response variables - Age and Location, which are numerical and categorical variables respectively.
Explanatory
What is the explanatory variable, and what type is it (numerical/categorival)?
The explanatory variables are 1) number of incidences for age groups 2) number of incidences for death locations classified as rural
Relevant summary statistics
All variables which have been captured in study.
names(AllAbuseData)## [1] "CaseNumber" "Date"
## [3] "Sex" "Race"
## [5] "Age" "Residence.City"
## [7] "Residence.State" "Residence.County"
## [9] "Death.City" "Death.State"
## [11] "Death.County" "Location"
## [13] "DescriptionofInjury" "InjuryPlace"
## [15] "ImmediateCauseA" "Heroin"
## [17] "Cocaine" "Fentanyl"
## [19] "Oxycodone" "Oxymorphone"
## [21] "EtOH" "Hydro.codeine"
## [23] "Benzodiazepine" "Methadone"
## [25] "Amphet" "Tramad"
## [27] "Morphine..not.heroin." "Other"
## [29] "Any.Opioid" "MannerofDeath"
## [31] "AmendedMannerofDeath" "DeathLoc"Description of Age
describe(AllAbuseData$Age)## vars n mean sd median trimmed mad min max range skew kurtosis
## X1 1 3043 41.77 12.34 42 41.65 14.83 14 87 73 0.07 -0.84
## se
## X1 0.22A graph showing distrubution of cases by age.
ggplot(AllAbuseData, aes(x=Age)) + geom_histogram()
Listing the names of counties in drug data.
unique(AllAbuseData$Residence.County)## [1] WINDHAM LITCHFIELD HARTFORD
## [4] NEW HAVEN MIDDLESEX FAIRFIELD
## [7] TOLLAND DUTCHESS
## [10] NEW LONDON PUTNAM MUSCOGEE
## [13] USA NORFOLK HILLSBOROUGH
## [16] MIAMI-DADE ORANGE WESTCHESTER
## [19] QUEENS NEW CASTLE COOK
## [22] HAMPDEN NEW YORK WINNEBAGO
## [25] ESSEX COLLIER SARATOGA
## [28] LOS ANGELES DAKOTA CHESAPEAKE CITY
## [31] SANTA CRUZ WORCESTER MADISON
## [34] ST JOHN THE BAPTIST BERKSHIRE CUMBERLAND
## [37] CUYAHOGA HARRIS SUFFOLK
## [40] NASSAU LAKE PASSAIC
## [43] KINGS GLOUCESTER Hartford
## [46] New Haven AROOSTOOK Fairfield
## [49] NEWPORT Windham Tolland
## [52] Middlesex Litchfield PROVIDENCE
## [55] KNOX WESTMORELAND ROGERS
## [58] OCEAN ULSTER WASHINGTON
## [61] WELD
## 61 Levels: AROOSTOOK BERKSHIRE CHESAPEAKE CITY COLLIER ... WORCESTERunique(AllAbuseData$Residence.City)## [1] ONECO WINCHESTER AVON
## [4] NEW HAVEN MIDDLETOWN NEWTOWN
## [7] HAMDEN MERIDEN HARTFORD
## [10] NORTH CANAAN WETHERSFIELD STAMFORD
## [13] ENFIELD WATERBURY CHESHIRE
## [16] SOUTHINGTON NEW BRITAIN MANCHESTER
## [19] VINE GROVE NEWINGTON BROOKLYN
## [22] WALLINGFORD VERNON
## [25] WILTON CLINTON GALES FERRY
## [28] SOUTH WINDSOR PLAINVILLE STANFORDVILLE
## [31] WEST HARTFORD WOLCOTT GUILFORD
## [34] ANDOVER EAST HAMPTON DAYVILLE
## [37] WEST HAVEN LEBANON NEW LONDON
## [40] WILLIMANTIC BRIDGEPORT RIDGEFIELD
## [43] COVENTRY SEYMOUR ELLINGTON
## [46] MIDDLEBURY NORWICH NAUGATUCK
## [49] SHELTON TORRINGTON BREWSTER
## [52] OLD LYME THOMASTON MILFORD
## [55] EAST HAVEN STRATFORD WATERTOWN
## [58] BRISTOL DANBURY COLUMBUS
## [61] LISBON WINDSOR LOCKS PROSPECT
## [64] ANSONIA NEW MILFORD SALEM
## [67] GREENWICH DEEP RIVER NORTH HAVEN
## [70] KILLINGWORTH SALISBURY PITTSBURGH
## [73] EAST WINDSOR VOLUNTOWN FARMINGTON
## [76] STAFFORD HARWINTON NIANTIC
## [79] UNCASVILLE EAST HARTFORD GLASTONBURY
## [82] GROTON WELLESLEY MARLBOROUGH
## [85] BRANFORD HANCOCK BOLTON
## [88] WINSTED FRANKLIN LEDYARD
## [91] WILLACOOCHEE JEWETT CITY BROOKFIELD
## [94] WATERFORD NEW BRIT SOUTH GLASTONBURY
## [97] DOVER PLAINS DANIELSON AVENTURA
## [100] TRUMBULL NORWALK NO HAVEN
## [103] ORANGE OAKDALE TERRYVILLE
## [106] OAKVILLE CANTON NORTH SALEM
## [109] MANSFIELD NEW FAIRFIELD COLCHESTER
## [112] DERBY SUFFIELD PRESTON
## [115] EAST CANAAN MOOSUP FLUSHING
## [118] MONROE TAFTVILLE MADISON
## [121] EAST LYME NEW CASTLE AMSTON
## [124] ROCKY HILL UNIONVILLE ROCKVILLE
## [127] TOLLAND ARLINGTON HEIGHTS MYSTIC
## [130] WASHINGTON CROMWELL PAWCATUCK
## [133] MONTVILLE BERLIN DURHAM
## [136] BALTIC NORTH GROSVENORDALE PORTCHESTER
## [139] FAIRFIELD PUTNAM WINDSOR
## [142] PORTLAND PALMER TARIFFVILLE
## [145] IVORYTON THOMPSON WOODBURY
## [148] S GLASTONBURY NEW YORK DARIEN
## [151] WINGDALE WOODBRIDGE PORT CHESTER
## [154] ESSEX BURLINGTON OSHKOSH
## [157] ALFRED STATION STAFFORD SPRINGS REDDING
## [160] SAUGUS POMFRET MORRIS
## [163] STAFFORD SPGS BOZRAH SUDBURY
## [166] PLAINFIELD N HAVEN SOMERS
## [169] QUAKER HILL JASPER NORTH BRANFORD
## [172] NORTHFORD OXFORD NEW BEDFORD
## [175] RYE VERNON ROCKVL HANOVER
## [178] SHERMAN EAST GRANBY WINDHAM
## [181] KILLINGLY SOUTHBURY NEW CANAAN
## [184] SAKEM BROAD BROOK CHESTER
## [187] EASTFORD HEBRON DEER LODGE
## [190] BEACON FALLS EAST HADDAM WESTPORT
## [193] WATERBRUY HURLEY SIMSBURY
## [196] ALLSTON BETHEL OLD SAYBROOK
## [199] MILLERTON STERLING BASS HARBOR
## [202] BETHANY SHARON CANTERBURY
## [205] ZIONSVILLE EAST WOODSTOCK COLUMBIA
## [208] WESTBROOK NAPLES SARATOGA SPGS
## [211] EAST BERLIN CHARLESTOWN BLOOMFIELD
## [214] PLANTSVILLE HAWAIIAN GARDENS INVER GROVE HEIGHTS
## [217] MOODUS HADDAM CHESAPEAKE
## [220] OLD GREENWICH WEST HAVEN WILLINGTON
## [223] ROGERS GOSHEN SANTA CRUZ
## [226] EAST HARTLAND MAPLEWOOD GRISWOLD
## [229] GRANBY GROTON LONG POINT WEBSTER
## [232] SANDY HOOK PAWTUCKET W HAVEN
## [235] NORTH STONINGTON QUINCY ORLANDO
## [238] TACONIC ASTORIA HAMPTON BAYS
## [241] PLYMOUTH EAST MEADOW KINGSTON
## [244] CANAAN WEATOGUE SPRAGUE
## [247] QUINEBAUG COLLINSVILLE MAHOPAC
## [250] SOUTH LYME HAMILTON LITCHFIELD
## [253] NUTLEY FALLS VILLAGE KENSINGTON
## [256] CHICOPEE LA PLACE GRANVILLE
## [259] MELROSE WESTON LEOMINSTER
## [262] PITTSFIELD MT VERNON CHAPLIN
## [265] YORKTOWN HEIGHTS STONINGTON SOUTHPORT
## [268] NOANK VINELAND MILLDALE
## [271] PARMA KINGWOOD NEW HARTFORD
## [274] CHELSEA WILLISTON PARK CLERMONT
## [277] MIDDLEFIELD PASSAIC BANTAM
## [280] RED HOOK NEWFIELD HODGDON
## [283] NEWPORT WOODSTOCK CHEPACHET
## [286] WHITE PLAINS HIGGANUM ASHFORD
## [289] KNOXVILLE VANDERGRIFT CLAREMORE
## [292] HOUSTON JACKSON EASTON
## [295] HIGHLAND RICHMOND COS COB
## [298] MILLIKEN WEST SUFFIELD
## 299 Levels: ALFRED STATION ALLSTON AMSTON ANDOVER ... ZIONSVILLE