study designs _population sampling
TRANSCRIPT
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Dr. LakshmiAssistant Professor
(Epidemiology)School of Public HealthP!"E#$ %handigarh
Study designs in Epidemiology
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!nitial &uestions
Appropriate studydesign
Sample si'eSampling
Data collection
Data analysis
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irst Step *b+ecti,e of thestudy-urden of the disease
Hypothesis generationEg /hat is the health seeking
beha,iour of chestsymptomatics in acommunity0
Association
Eg /hat are the risk factors ofdeath after 1- treatment0
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-urden of Disease or Hypothesiseneration %ross2sectional
studiesPro,ide snap shot ofpopulation at a singlepoint of time
E3posure and disease
assessment at thesame point
*utcome "easurementPre,alence
"easure of associationPre,alence ratio orodds ratio
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E3ample#esearch &uestion 1o 4nd out the
pre,alence of chest symptomatics in urbanand rural areas
%onduct the sur,ey in urban and rural areas
Estimate the chest symptomatics in eacharea
!f chest symptomatics are more in rural
area$ 5e can generate hypothesis thatresiding in rural area causes prolongedcough
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%ross sectional Sur,eys %hestSymptomatics$ 67 years and abo,e
Place Sur,eyed
%hestsymptomatics
8
%ity 799 7 6
1o5n 799 :6.;
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Limitations %ross2sectionalstudies
%annot distinguish temporalse=uence of e3posure and disease
A>ected by factors in?uencingpre,alence
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Association AnalyticalStudies%ase control%ohort
!nter,entional studies
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%ase2%ontrol Studies
Controls
No Exposure
Exposure
Cases
Exposure
No Exposure
Assess Select
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%ase %ontrol Study E3ample#esearch &uestion 1o 4nd out the riskfactors for death after 1- treatment%ases Deaths after 1- treatment
%ontrols 1hose sur,i,ed after 1-treatment
E3posure or E3ample$ Smoking
%ompare odds of smoking amongcases and controls by calculating *dds#atio
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*dds of Smoking among Deaths77@6
*dds of Smoking among Sur,i,ors@
DEATHS SURVIVORS
Hypothetical Case Study: Aon! ten deaths o"
T# "ollo$in! treatent% "i&e $ere so'ers(
Aon! )* people $ho sur&i&ed a"ter T#
treatent + $ere so'ers(
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%ase control studies"easure of association *dds ratio
Cases(Deaths)
Controls(Survivors)
Exposed(Smokers)
5(a) 2(b)
NotExposed
(Nonsmokers)
5(c) 8(d)
Odds o
Exposure
5!5(a!c) "# 2!8(b!d)"$%
25*dds #atio @ (ac) (cd) @ 69.;7@B
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%ase control studiesAd,antages/hen aetiology is unkno5nLess time and money
#are diseases and diseases 5ith longlatent periodsDynamic population
Disad,antages
DiCcult to establish temporal se=uence#are e3posuresreater chance of bias
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%ohort studies
Exposed
Unexposed
Diseased
Not Diseased
Diseased
Not Diseased
AssessSelect
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%ohort studies
Prospecti,eE3posed and ne3posedpopulations follo5ed into future for
the de,elopment of outcome#etrospecti,eE3posure and outcome ha,e
already occurred-asic study design is al5ays frome3posure to disease
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E3ample
#esearch &uestion 1o kno5 the risk factors fordeath after treatment for 1-
%ohort All ne5ly diagnosed cases of 1- 5ho5ere kept on D*1S and completed thetreatment and follo5ed to see ho5 many died
after treatmentE3posure or e3ample$ Smoking
*utcome Death after treatment 5ith 1-
Di,ide the cohort into smokers and non smokers
%alculate risk of dying in each group andcompare by using #elati,e risk
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#isk of dying among [email protected]
#isk of dying among onsmokers@
S,O-ERS NON S,O-ERS
Hypothetical Case Study: Aon! ten so'ers
$ho had treatent "or T# . died a"ter treatent
$ith T# $hereas aon! )* non so'ers only +
died
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%ohort studies"easure of association #elati,e risk
Deaths
Survived
&otal
'isk
Exposed(Smokers)
5(a) 5(b) #$(ab)
5!#$"$%5
Not
Exposed(Nonsmokers)
2(c) 8(d) #$
(cd)
2!#$
"$%2
#isk of dying among smokers 769 (aaFb)@ 9.7
#isk of dying among on smokers ;69
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%ohort studiesAd,antages#are e3posuresDirect estimation of riskLess chance of -ias (Prospecti,e)
"ultiple e>ects of a single disease/ell de4ned temporal se=uenceDisad,antages 1ime consuming costly (Prospecti,e)#are outcomes long latent periods
(Prospecti,e)-ias (#etrospecti,e)Poor information on e3posures and
outcomes (#etrospecti,e)
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!nter,ention studies!n,estigator assigns e3posure to the
participants
Study design is from e3posure to outcome
Ethical problems for ha'ardous e3posuresStudied by attempts to eliminate the
e3posures
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!nter,ention studies
Ad,antages"ost reliable e,idence in
epidemiological research becausethe e3posure is randomly assigned#andomisation controls the e>ectsof the risk factors not considered atthe time of the study.
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Sampling
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Sampling "ethods
Simple #andomSampling
Systematic #andomSampling
Strati4ed #andom
Sampling"ulti Stage sampling
%luster sampling
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Simple #andom Sampling
E=ual probability of selection
Sampling frame re=uired
#andom number table%alculator%omputer
9G B BG G :
I B ;B : :; 6: : :; ; ::
6; 7: 7 II ;:
77 7I 7: G7 :B
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Systematic #andomSamplingo sampling frame re=uiredPrecision similar to S#S
1otal population di,ide by sample si'e to getthe sampling inter,al (G99G9@69)
#andom sample of a sampling unit bet5eenthe 4rst unit and the sampling inter,al (6269)
Subse=uent units selected by adding thesampling inter,al in the 4rst random selectedunit$ and then in the second unit and so on.
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Strati4ed SamplingS#S represents strata in the same
proportion as in the populationSeparate estimate may be re=uires for
each stratum (rural$ urban)
Di,ide the sample frame into stratase S#S or systematic random sample to
dra5 sample in each strata/eighted a,erage of the estimate stratum
estimates gi,es population estimates
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"ulti stage Sampling
15o stage4rst stage of administrati,e units (PSs)Second stage of the sampling units in the PS
1hree or multi stage
S#S or Systematic #andom Sampling method usedfor ,arious stage sample units
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Sample si'e
"easurement of interest
Pre,alence$ !ncidence$ "ean$Proportion$ *#$ ##
J K error
#e+ecting ull Hypothesis 5hen it istrue
sually 78 9r 68
K error
ailing to re+ect ull Hypothesis5hen it is false
Po5er@ 62 $ usually 98 9r I98
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Statistical Analysis
-inarySingle Proportion 15o Proportions&uantitati,eSingle "ean 15o "eansDistribution
ormalot ormal
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1est of Signi4cance
"eanSingle M t test 15o M t testPaired Paired t test
"ore than t5o A*