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Sampling
Bogor, May 23, 2012
Module 11
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S t e p s
i n t h e d e
v el o pm en
t of a
H S R p
r o p o s al
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Objectives
At the end of the session, you should be able to:
Identify and define the population(s) to be studied
Identify and describe !ommon methods of sampling
Discuss problems of bias that should be a"oided #hensele!ting a sample
List the issues to !onsider #hen de!iding on samplesi$e
Decide on the sampling method(s) and sample si$e(s)
most appropriate for the resear!h design you arede"eloping
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I. I!ROD"#!IO
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$H%! is samplin&'
%he pro!ess of sele!ting a number ofstudy units from a defined study
population
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Sample types
&f study population is small, total populationsample (eg All M'%B patients in the *M'%program)
&f study population is lar&e, mainly forpra!ti!al reasons, sample of the population
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Samplin& (uestions
+hat is the group of people (S%'-*.*/A%&.) #e are interested in from#hi!h #e #ant to dra# a sample
o# many people do #e need in oursample
o# #ill these people be sele!ted
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Study population
Should be !learly defined, for eample,a!!ording to age, se, and residen!e
4onsists of study units
5 *ersons
5 6illages
5 &nstitutions
5 *atient re!ords
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Representative sample
A sample #ith all the important!hara!teristi!s of the population from#hi!h it is dra#n
)or e*ample+
&f you study health !are see7ing beha"iour in 100 %Bpatients in 8ast 9a"a you #ould ha"e to sele!t these %Bpatients from a representati"e sample of "illages!ities
&t #ould be un#ise to sele!t them from the !apital !ity asthis might gi"e you a distorted (biased) pi!ture
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Definitions
Study population
5 All the sampling units or indi"iduals#hi!h !ould possibly be in!luded in the
sample Samplin& unit
5 %he item #hi!h is sampled
Samplin& interval5 %he proportion of a study population
sampled
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II. S%M,LI- M!HODS
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Samplin& methods
*urposi"e sampling strategies for(ualitative studies
andom sampling strategies to !olle!t
(uantitative data
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,urposive samplin& strate&ies
;o!using on limited number of informants,#hom #e sele!t strategically
%heir indepth information gi"es optimal
insight into an issue about #hi!h little is7no#n
ote: not representati"e of the general
population<
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,urposive samplin& strate&ies
8treme !ase sampling
Maimum "ariation sampling
omogeneous sampling
%ypi!al !ase sampling
4riti!al !ase sampling
Sno#ball or !hain sampling
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*treme case samplin&
A sele!tion pro!ess that in!ludesunits #ith spe!ial or unusual!hara!teristi!s
8g &nter"ie#ing good or "ery poor !ompliers to%B treatment help in identifying !ontributing
fa!tors to poor !omplian!e
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Ma*imum variation samplin&
A sele!tion pro!ess #hi!h in!ludes units sothat differen!es on spe!ified !hara!teristi!sare maimi$ed
8g ;or studying reasons for defaulting #e sele!tmales and females, poor and ri!h, indi"iduals#ith rural and urban residen!e et!
'oes not pro"ide representative data for thetotal population
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Homo&eneous samplin&
A sele!tion pro!ess fo!using on parti!ularunit or subgroup !onsideredhomogeneous
8g Sele!tion of urban poor people to study theeffe!t of the introdu!tion of user fees on health!are see7ing beha"ior
sed for ;o!us =roup 'is!ussions: parti!ipantsdis!uss more freely #hen they are amongstpeople of similar so!ial status
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!ypical case samplin&
A sele!tion pro!ess that in!ludes units!onsidered typi!al of the phenomenonunder study
8g Study of performan!e of a %B !lini! in a slumarea
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#ritical case samplin&
Sampling of those indi"iduals #ho >!anma7e the differen!e? #ith respe!t to aninter"ention you #ant to introdu!e or toe"aluate
8g -ou #ant to introdu!e leaflets eplaining theimportan!e of nutrition for %B patients %heseleaflets !an be tested on malnourished %B
patients
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Sno/ball or chain samplin&
&nter"ie# sub@e!ts are obtained fromsub@e!ts already inter"ie#ed for the study
eg &ndepth inter"ie# leads to dis!o"eries #hi!hseem re#arding to follo#up by a number ofinter"ie#s #ith an additional group of informants
.ften used in diffi!ulttorea!h populations(homeless, in@e!ting drug users, )
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,robability samplin& strate&ies
&f #e #ant to &eneralise the findingsobtained from a sample to the total studypopulation
ses random sele!tion pro!edures toensure that ea!h unit of the sample is!hosen on the basis of !han!e
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,robability samplin& methods
Simple random sampling
Systemati! sampling
Stratified sampling 4luster sampling
Multistage sampling
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Simple random samplin&
sed in situations #here the number of samplingunits is relati"ely small
'etermine units a"ailable for sampling: ie Studypopulation of 100 indi"iduals
'e!ide on sample si$e: ie Sample 10 indi"iduals
/ottery method (random number table, !omputerprogram
01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50
51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75
76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99
100
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%dvanta&es and Disadvanta&es
Ad"antages
5 8asy to understand
5 8asy to analy$e
'isad"antages
5 euires a list of the population
5 4ost may be prohibiti"e
5 May miss or undersample 7ey subsets
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%dvanta&es and Disadvanta&es
Ad"antages
5 /ess time !onsuming than simple randomsampling
5 8asy to perform
'isad"antages
5 is7 of bias (ie sampling days of the #ee7#ith sampling inter"al of C #ill al#ayssele!t %uesday #hi!h may be a mar7etday)
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Systematic samplin&
A systemati! sample is sele!ted from 100 studentsof a s!hool %he sample si$e sele!ted is 2D
2D (E sample si$e)
100 (E study population)2D100EF, sampling inter"al
Start at random student bet#een 1 and F, eg 2
01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50
51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75
76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99
100
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Stratified Samplin&
sed #hen the sampling frame !ontains!learly different !ategories (strata), eg
5 rban and rural fa!ilities
5 4ommunity and prison patients
seful if !omparisons #ill be made of theresults in subgroups of the studypopulation
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Stratified samplin&
1 G 11 1G 21 2G 31 1 G 11
2 12 1 22 2 32 2 12
3 H 13 1H 23 2H 33 3 H 13F I 1F 1I 2F 2I 3F F I 1F
D 10 1D 20 2D 30 3D D 10 1D
!0 prevalence surveyural 3D "illages
rban 1D !ities
Sele!t D "illages and D !ities
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Stratified samplin&
1 G 11 1G 21 2G 31 1 G 11
2 12 1 22 2 32 2 12
3 H 13 1H 23 2H 33 3 H 13
F I 1F 1I 2F 2I 3F F I 1F
D 10 1D 20 2D 30 3D D 10 1D
!0 prevalence survey
ural 3D "illages
rban 1D !ities
Sele!t D "illages and D !ities by simple randomsampling
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Stratified samplin&
1 G 11 1G 21 2G 31 1 G 11
2 12 1 22 2 32 2 12
3 H 13 1H 23 2H 33 3 H 13
F I 1F 1I 2F 2I 3F F I 1F
D 10 1D 20 2D 30 3D D 10 1D
!0 prevalence surveyural 3D "illages
rban 1D !ities
Sele!t D "illages and D !ities by systemati! sampling
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%dvanta&es and Disadvanta&es
Ad"antages
5 4an dra# !on!lusions about relati"elysmall group
'isad"antages
5 More time !onsuming
5 neual sampling fra!tions: must be
!orre!ted for if generali$ing findings to#hole population
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#luster Samplin&
sed #hen for logisti! reasons it is easierto sele!t sample units in groups5 =eographi!: distri!ts"illages5 .rganisational units: s!hools!lini!s
Method5 &dentify !lusters of units of interest5 Sele!t !lusters of sample units randomly
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#luster samplin&
1 2 3 F D G H I 10
11 12 13 1F 1D 1G 1 1H 1I 2021 22 23 2F 2D 2G 2 2H 2I 30
31 32 33 3F 3D 3G 3 3H 3I F0
F1 F2 F3 FF FD FG F FH FI D0
%uber!ulin sur"ey #ith 1,000 !hildren
&n total D0 s!hools in the region
Sele!t 10 s!hools
Sele!t 100 !hildren per s!hool
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#luster samplin&
1 2 3 F D G H I 10
11 12 13 1F 1D 1G 1 1H 1I 2021 22 23 2F 2D 2G 2 2H 2I 30
31 32 33 3F 3D 3G 3 3H 3I F0
F1 F2 F3 FF FD FG F FH FI D0
%uber!ulin sur"ey #ith 1,000 !hildren
&n total D0 s!hools in the region
Sele!t 10 s!hools by simple random sampling
Sele!t 100 !hildren per s!hool
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Multista&e samplin&
Sample si2e 1345333 individualsStratifi!ation of distri!ts (urban, rural, remote)
Sorting all GIF distri!ts by population si$e
Stage 1, systemati! sampling of 0 distri!ts: 20urban, 30 rural, and 20 remote distri!ts
Stage 2, random sele!tion of 1 !ommune perdistri!t
Stage 3, random sele!tion of 1 sub!ommuneper !ommune
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0ias due to improper samplin&
Studying "olunteers only Sampling of registered patients only Missing !ases of short duration
Seasonal bias %arma! bias (a!!essibility)
onresponse
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III. S%M,L SI6
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Sample si2e
%he bigger the better
Sample si$e depends on:
5 8pe!ted "ariation in the data
5 4onfiden!e inter"al pre!ision needed
5 Si$e of target population
%he e"entual sample si$e is usually a
!ompromise bet#een #hat is '8S&AB/8and #hat is ;8AS&B/8
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Sample si2e calculations
Measuring one single "ariable in one group #ith a!ertain pre!ision (ie a mean, a rate or a proportion)
%rying to demonstrate a signifi!ant differen!e
bet#een groups
se of formula or table for !al!ulating sample si$e
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$hen to #alculate the Sample
Si2e &t is important to estimate the sample si$e
early in the design phase
+aiting until the last minute (or after thestudy
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Hypothesis !estin& ull hypothesis (o): %he proportion of
tuber!ulosis among smo7ers is notdifferent from nonsmo7ers
Alternati"e hypothesis (A): %he
proportion of tuber!ulosis among smo7ers
is greater than among nonsmo7ers (onesided)J . is different than among nonsmo7ers (t#osided)
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!ype I rror 7 probability of !ype I error (falsepositi"e error
rate)
8"en if the null hypothesis is %8, #e #ill, inrepeated samples, re@e!t o a proportion 8 of the
time
%raditionally, 8 9 3.34 5 the probability ofma:in& a !ype I error
5 %hus, the li7elihood of erroneously re@e!ting the nullhypothesis is DK
1 L E IDK !onfiden!e le"el
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!ype II rror ; ,o/er
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!ype II rror ; ,o/er
%raditionally, < 9 3.?35 the probabilityof ma:in& a !ype II error
%hus, there is a 20K !han!e of ma7ing a
%ype && error and failing to re@e!t the nullhypothesis #hen the alternati"e is true
%herefore, the po#er E (1020) E 0H0 orH0K (!han!e of dete!ting a differen!e of
the magnitude spe!ified if one truly eists)
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$hat else do /e need'
8pe!ted differen!e bet#een 2 groups
.ther, similar studies
*ilot study
An informed best guessN or estimate ofan important differen!eN
8pe!ted "ariability in the measurements
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)ormula+ #omparin& ?proportions
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Sample si2e in (uantitative studies
#omparin& t/o &roups for a si&nificant difference
%o !ompare the differen!e in B4= immuni$ation !o"eragebet#een t#o regions
1 8stimate !o"erage in both regions (say G0K (p0) and H0K
(p1))2 4hoose the li:elihood =study po/er> that the
"a!!ination !o"erage in the t#o regions is indeed different(say I0K)
3 nE (G0 x F0OH0 x 20) x (12HO1IG)2 E 10D
(H0G0) 2
#onf.
level
2 =1 8> po/er 2 =1
I0K 1GFD H0K 0HF
IDK 1.@A I0K 12H
(a)
Sample size for comparison of proportions in two groups
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Percentage 1
10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Percentage 2
5% 577 97 43 25 15 10
10% 262 79 38 22 14
15% 913 1207 157 62 32 19 1220% 262 388 105 48 26 16
25% 129 1459 1669 199 73 37 21 12
30% 79 388 472 121 52 28 16
35% 53 181 1837 1963 223 79 37 20 11
40% 38 105 472 514 126 52 26 14
45% 29 68 213 2047 2089 227 77 35 17
50% 22 48 121 514 514 121 48 22 10
55% 17 35 77 227 2089 2047 213 68 29 13
60% 14 26 52 126 514 472 105 38 16
65% 11 20 37 79 223 1963 1837 181 53 19
70% 16 28 52 121 472 388 79 24
75% 12 21 37 73 199 1669 1459 129 31
80% 16 26 48 105 388 262 4285% 12 19 32 62 157 1207 913 59
90% 14 22 38 79 262 94
95% 10 15 25 43 97 577 199
100% 10 16 24 42 94
u= 1.28 Power=90%
v= 1.96 Significance: P
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)ormula+ sin&le proportion
n E P2 p
d2
P E 1IG, the normal "alue !orresponding to theIDK !onfiden!e inter"al
* E 0H0, pre"alen!e from the abo"e study
E 1p E 020
d E margin of error E desired pre!ision E 002D
n E 1IG2 (0H Q 02) E IHF 0,02D2
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Other Increases ecessary in
Sample Si2e Determination
emember to a!!ount for:
nonparti!ipation (usually estimatedat 101DK)
loss to follo#up (in a !ohort study)#hi!h !an be substantial
other issues su!h as inability to find!harts, et!
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sampsi 0G 0D, alpha(00D) po#er(0I0)
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http:sampsi$esour!eforgenet
http://sampsize.sourceforge.net/http://sampsize.sourceforge.net/http://sampsize.sourceforge.net/
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-RO", $ORB
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=.* +.R, *A% & (2 hours)
'e"elop in your #or7ing group:
a definition of your (different) study population(s)J
a definition of your (different) study units (people, !lini!s,re!ords, et!)J
appropriate sampling pro!edures for your study, ta7inginto a!!ount #hether you use ualitati"e andoruantitati"e resear!h methods State ho# you #ill try toa"oid possible bias
*repare a summary on a flip!hart for use in the eer!ise
>4ommenting on ea!h others sampling pro!edures? and inthe plenary dis!ussion (after group #or7 on sample si$e)
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=.* +.R, *A% && (1 hour)
'etermine the sample si$e reuirements for the studypopulation(s) defined in the pre"ious group #or7 session
'etermine the feasible sample si$e after ta7ing intoa!!ount a"ailable time, manpo#er, transport and money
&f there is a large dis!repan!y bet#een the desirable andthe feasible sample si$e you should loo7 for a!ompromise and, if ne!essary, ad@ust the ob@e!ti"es ofyour study
*ut a summary of your groups #or7 on flip!hart for use
in the eer!ise belo# and in the plenary dis!ussion that#ill follo#