population sampling rss6 2014

Population Sampling

Dr Fayssal M Farahat MD, MSc, PhD

Public Health Consultant

Infection Prevention and Control Department Associate Professor, Faculty of Medicine, Menoufia University, Egypt

Research Fellow, Oregon Health & Science University (OHSU), USA

Complete set of people

with a specified set

of characteristics SAMPLE

=

Subset

of

The

population

Clinical & demographic

Teenagers with asthma

Teenagers with asthma

living in Jeddah in 2013

Population

Study

subjects

Truth in the universe

Target

population

Findings in the study

Generalisability

Infer

Study

subjects


Target

population

Generalisability

design

Specify

clinical,

demographic,

& geographic

characteristics


Specify accessible

population

and

approach

to select them

Study

subjects

Target

population

FIRST

Whether the sample differs from the population

Workers General

population

Study

subjects


Target

population


SECOND

Validity of generalizing from study subjects to target population

Infer Association

bet HTN & CHD

in a sample

of Jeddah adults

Same

Association

Exists in

Saudi adults

IS IT .. Can Be .. • No sample is the exact mirror

image of the population.

• Select samples with acceptable

errors.

Representative Generalized

Inclusion criteria • Main characteristics of the target

population.

Clinical Demographic

Age, sex, Race Geographic

A 5-year trial of

calcium supplementation

for preventing osteoporosis

Demographic

Clinical

Geographic

Temporal

White females 50 – 60 ys

In good general health

Patients attending PHC Jeddah

Bet Jan 1 – Dec 31 of next year

Men Black female

HTN Paraplegia Metastatic lung dis

• Including alcoholics in the

osteoporosis study would expand

generalizability and allow to study

alcohol consumption as a cause of

demineralization.

• Exclude alcoholics to avoid a big

problem due to loss of follow-up.

• Exclusion in clinical trials is more specific

and may be mandated by ethical

considerations.

BE CAREFULL ..!

• EXCLUSION might threaten the validity of

generalizing the findings to the population.

Sampling ..

Sampling ..

Minimal cost

Maximum speed

Maximum accuracy

Impossible to examine the entire population

Terminology

• Sampling unit (element) – Subject under observation on which

information is collected • Example: children <5 years, hospital discharges,

health events…

• Sampling fraction – Ratio between sample size and population

size • Example: 100 out of 2000 (5%)

Terminology

• Sampling frame

– List of all the sampling units from which sample is drawn

• Lists: e.g. children < 5 years of age, households, health care units…

• Sampling technique – Method of selecting sampling units from

sampling frame • Randomly, convenience sample…

Samples Probabilty

Non Probabilty

Samples Probability

Non Probability

Probability

of selection

KNOWN

Probability

of selection

UNKNOWN

Non probability samples

Convenience

Quota

Snowball

Some elements of the population have no chance of selection “out of coverage”

ease of access

friend ….etc

Specific quota for

subgroup

Purposive Purpose

Convenience samples

Consecutive design

a practical approach for most clinical research projects

Entire accessible population over a long enough period

Avoid seasonal variations

Avoid changes over time

Generalisability

Gold Standard for

Probability Sampling

Each unit has specified

chance of selection

RANDOM

the choice of one subject will

not affect the chance of other

subjects being chosen

RANDOM

Generalisability

Sampling

RANDOM

Simple Random Sample عينة عشوائية بسيطة

Systematic Sample (متوالية)عينة عشوائية منتظمة

Stratified Random Sample عينة عشوائية طبقية

Cluster Sample عينة عشوائية عنقودية

Random Sample

Multistage sample عينة عشوائية متعددة المراحل


Ideal Bowel

Random number table

Computer-generated

Simple random sampling

57172 42088 70098 11333 26902 29959 43909 49607

33883 87680 28923 15659 09839 45817 89405 70743

77950 67344 10609 87119 15859 74577 42791 75889

11607 11596 01796 24498 17009 67119 00614 49529

56149 55678 38169 47228 49931 94303 67448 31286

80719 65101 77729 83949 83358 75230 56624 27549

93809 19505 82000 79068 45552 86776 48980 56684

40950 86216 48161 17646 24164 35513 94057 51834

12182 59744 65695 83710 41125 14291 74773 66391

13382 48076 73151 48724 35670 38453 63154 58116

38629 94576 48859 75654 17152 66516 78796 73099

60728 32063 12431 23898 23683 10853 04038 75246

01881 99056 46747 08846 01331 88163 74462 14551

23094 29831 95387 23917 07421 97869 88092 72201

15243 21100 48125 05243 16181 39641 36970 99522

53501 58431 68149 25405 23463 49168 02048 31522

07698 24181 01161 01527 17046 31460 91507 16050

22921 25930 79579 43488 13211 71120 91715 49881

68127 00501 37484 99278 28751 80855 02035 10910

55309 10713 36439 65660 72554 77021 46279 22705

92034 90892 69853 06175 61221 76825 18239 47687

50612 84077 41387 54107 09190 74305 68196 75634

81415 98504 32168 17822 49946 37545 47201 85224

38461 44528 30953 08633 08049 68698 08759 45611

07556 24587 88753 71626 64864 54986 38964 83534

60557 50031 75829 05622 30237 77795 41870 26300

Table of random numbers

1200

Students

100


Random Sample

Select sample at regular

intervals based on sampling

fraction.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

31 32 33 34 35 36 37 38 39 40 41 42 43 44 45

16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

46 47 48 49 50 51 52 53 54 55 ……..

• N = 1200, and n = 60

1200/60 = 20

• List persons from 1 to 1200

• Randomly select a number between 1 and 20 (ex : 8)

1st person selected = the 8th on the list

2nd person = 8 + 20 = the 28th

etc .....


Systematic sampling


Random Sample

Stratified sampling

• When the sampling frame contains

clearly different categories (strata)

– Males and females

– Social classes

• What we do : – Classify population into internally

homogeneous subgroups (strata)

– Draw sample in each strata

Stratified sampling

Equal vs.

proportional

allocation.

Stratified sampling (example)

• N=12000 K=3

• N1=6000 N2=4000 N3=2000

• N=240

• n1= (240×6000)/12000 = 120

• n2= (240×4000)/12000 = 80

• n3= (240×2000)/12000 = 40


Random Sample

–In selected clusters, all units or

proportion (sample) of units

included.

–All students in a classroom.


Random Sample


– 1rst stage : drawing regions

– 2nd stage : drawing city from each region.

– 3rd stage : drawing areas from each city.

– 4th stage: drawing houses from each area.


Determine vaccination coverage in a country

Section 4

Section 5

Section 3

Section 2 Section 1





Random Sample


• Random sample of the gallbladder surgery

patients.

• Reviewing hospital records of patients with

lung cancer from allover the country.

The use of random numbers is

generally preferable to using

systematic random.

Agree Dis-agree

The use of random numbers is

generally preferable to using

systematic random.

Agree

The regularity of selection can coincide by chance with some

unforeseen regularity in the presentation of the material for study –

Hospital appointments being made from patients

from certain practices on certain days of the week

2nd Advanced Course on Applied Medical Research and Biostatistics 22 – 24 March 2010 50

The Errors of Research

No study is free of errors

The goal is to maximize the validity

The best is to prevent errors from occurring (design & Implementation)

Errors can be addressed in the analysis


Random Error

Wrong result due to chance

20% 18

19

21

22

28

12

Sample Size

precision


Systematic Error

Wrong result due to BIAS

Sample (respondents) or

Measurement (unclear Q)

OR

Accuracy

Sample size

Response rate

= proportion of eligible persons who

agree to enter the study.

People difficult to reach.

People refused to enter.

…..

?

25%

• Acquire additional information on the non-

respondents.

or best

• Deal with non-response bias at the outset

Deal with non-response bias at the outset

• Series of repeated contacts (mail, telephone, home visit).

• Choosing a design that avoids invasive and uncomfortable tests.

• Using brochures and discussion to minimize the anxiety and discomfort.

• Providing incentives (reimbursing the costs of transportation and providing the results of the tests).

To anticipate ..

• Pre-test help to estimate the response rate

and how much to increase to get your

required sample.

• During the actual study, monitor the non-

response and find solutions to overcome

before continue to next sample.

Who will be included

Technique

of selection

How many ..?

Practical issues • Allow for drop-outs and non-consent

when planning sample size,

particularly when subjects are being

followed up for a long period of time.

• A pilot study may be necessary to

obtain suitable estimates.

Dr. Fayssal Farahat

Thank you

Email:

[email protected]

[email protected]

population sampling rss6 2014

Health & Medicine

population sampling

study generalisability

sampling units

osteoporosis study

probabilty samples probability

clinical demographic

sample of jeddah adults

clinical trials