Survey and Sample Size Calculation in Epidemiological Studies.pptx

Survey and Sample
Size Calculation
MUHAMMAD SAYYAM AKRAM
DEPARTMENT OF POULTRY SCIENCE

Contents of
Discussion:
Introduction To Survey
Steps In Carrying Out A Survey
Advantages And Disadvantages Of Surveys
Sources Of Error
Major Take-Home Points (Shortcuts To
Avoid)
SURVEYAND SAMPLE SIZE CALCULATION 2

Introduction To Survey
What is a Survey?
How to start a Survey?
How we can classify Surveys?

What is a Survey?
• A survey is a canvassing of people for the purpose of collecting information.
• Surveys are done when there is a question to be answered, and there is no existing
data source to provide the needed information.
• A survey is a lot of work and should never be conducted when the information can be
obtained more readily elsewhere.
• Therefore, it is important to investigate thoroughly the availability of
existing data before undertaking a survey.
According to CAMBRIDGE dictionary;
To ask people questions in order to find out about their opinions and behaviors.

How to start a Survey?
A good place to start is to contact a:
• National statistical office,
• Census bureau,
• Ministry of health,
• Other governmental organizations that would have
knowledge of large data collection efforts and the
availability of existing data.

How we can classify Surveys?
Surveys can be classified in a
number of ways.
Census or A Complete Population Survey
 Every element in the target population is
included.
 Extremely expensive and is rarely used to
collect detailed information from a large
population.
Sample Survey
 Only a portion of the target population is
selected.
 Less expensive and less time consuming.
 Large health-related surveys are also
sample surveys.

Steps In Carrying Out A Survey
1. Write a protocol.
2. Select a survey mode.
3. Develop a questionnaire.
4. Design and select the sample.
5. Train interviewers
6. Collect data (fieldwork).
7. Enter data into a computer, edit, and
process the data.
8. Analyze the data.
9. Write a survey report.

1. Write A Protocol
A survey cannot be undertaken without a protocol or detailed plan.
The various steps in survey design are all interconnected and, therefore, must be thought
out carefully prior to beginning any steps of the survey itself.
The Protocol should include:
 Study Objectives;
• Methodology, including a list of information to be sought from the survey.
• Survey design
• Sampling plan
 Data editing plan;
• Analysis Plan, including the computer software necessary to analyze the data.
• Logistics for implementing the survey, including personnel and equipment needed.
 Budget and Time Line.

2. Select A Survey Mode
Surveys can be classified by their mode of data collection.
Prior to developing a questionnaire and choosing a sample, the survey mode must be decided.
Mail and Internet surveys
Telephone surveys
Face-to-face interview surveys.
03 Modes of a Survey

Mail, or self-administered, surveys are seldom used to collect information from public.
However, the method may be highly effective with members of particular groups, such as
members of an HMO (Health Maintenance Organization) or members of a Professional
Association.
Advantages:
• May obtain more thoughtful responses.
• Least expensive to implement.
Disadvantages:
• Obtains a much lower response rate (50% is not unusual for a mail survey).
• Computer survey is not a good choice for a general population survey.
(selectivity of persons who use or own computers)
Mail And Internet Surveys
Sometimes survey data are obtained with self-administered questionnaires that
are not mailed or sent over the Internet but are provided to respondents in person,

Telephone Surveys
Telephone interviewing is an efficient survey method and has become quite popular in the
United States.
Investigations of epidemics frequently rely on telephone surveys.
Advantages:
• Quick, inexpensive, and sensitive
• They quickly reveal whether a problem truly exists.
Disadvantages:
• The response rate for a telephone survey is not as high as that of a face-to-face
interview.
• Populations with and without telephones may differ, creating a possible important
bias.

Face-to-face Interview Surveys
A face-to-face interview is often the preferred or only feasible method of survey data
collection.
Advantages:
• High response rate (80%–95%)
• Permitting the collection of more complex and more sensitive information.
Disadvantages:
• The cost: interviewers’ salaries, their transportation, and, at times, their meals and
housing have to be considered.
• The potential for interviewer bias.
SURVEYAND SAMPLE SIZE CALCULATION
12
Survey can also be conducted (Mixed Mode Surveys):
 By combining telephone and mail or by telephone and face-to-face.
 It is highly recommended that you seek the assistance of a survey expert if you
choose to use a mixed mode approach.

3. Develop A Questionnaire
The first step in developing a questionnaire is to define the research question and to list the
information that you wish to obtain.
 You will also need to know the type of analysis you plan to use and the mode of data
collection.
 Your analysis plan will determine the form of responses to questions.
• If you plan to work with proportions, you will want to collect categorical responses.
• On the other hand, if you can work with means, you may collect scaled responses.
The mode of data collection (mail/Internet, telephone, or face-to-face interview) will
affect how the question is written, what response categories are shown, the length of the
questionnaire, and the overall format of the questionnaire.

General Rules On Question Writing
And Questionnaire Format
The question format
can be of three types:
Structured or closed-
ended questions.
Unstructured or open-
ended questions.
Pre-coded open-ended
questions.

Structured or closed-ended questions:
• These are questions that have predetermined response categories to choose from.
• The respondent is told what the response options are and is asked to choose from
among the options.
• Multiple-choice and true/false questions are examples of this format.
Unstructured or open-ended questions:
• This format allows the respondent to answer in his or her own words.
• The unstructured question is useful when the researcher does not know what the
range of response options might be.
• Coding and analysis of answers to open-ended questions can be very difficult and
time consuming.

Pre-coded open-ended questions:
• Open-ended questions that are pre-coded are often
used in interviewer-assisted surveys.
• These questions do not provide answer options to
the respondent, but have options written in the
questionnaire for the interviewer to circle or check
that correspond to the respondent’s stated answer.

Questionnaire Format:
• Often demographic questions are asked first to give
the respondent an opportunity to get comfortable
with the interviewer prior to being asked more
difficult or sensitive questions.
• Threatening or embarrassing questions should be
kept to a minimum and placed toward the end of the
questionnaire.
• If the respondent chooses not to answer these
questions, you will at least have obtained other
information asked earlier in the questionnaire that
you can use in analysis.

4. Design And Select The Sample
Sample:
• A representative part of a larger lot.
• A sample consists of a smaller group of entities, which are taken
from the entire population.
• This creates a subset group that is easier to manage and has the
characteristics of the larger population.
Why sampling?
• Sampling is a method that allows researchers to infer information
about a population based on results from a subset of the
population, without having to investigate every individual.
Reducing the number of individuals in a study reduces the cost and
workload, and may make it easier to obtain high quality
information.

Types of sampling
Non probability sampling
• Non-probability sampling techniques involve the researcher deliberately picking items
or individuals for the sample based on their research goals.
Convenience sampling:
• Convenience sampling is perhaps the easiest method of sampling.
• Participants are selected based on availability and willingness to take part. (Prone to
significant bias)
• Route samples, street-corner political surveys, or a sample based on persons coming
into a clinic are convenience samples.
Judgment (or Purposive) Sampling (Selective, or Subjective):
• This technique relies on the judgment of the researcher when choosing who to ask to
participate.
• Researchers may implicitly thus choose a “representative” sample to suit their needs.

Probability sampling:
Probability sampling, also known as random sampling, is a kind of sample selection where
randomization is used instead of deliberate choice.
Types of Probability sampling
Simple random sampling:
• Gives every member of the population an equal chance of being included in the
sample. It requires a listing of every member of the population. Once all members of
the population are assigned a number, a table of random numbers may be used to
select individuals for the sample
Systematic sampling:
• Individuals are selected at regular intervals from the sampling frame.
• The intervals are chosen to ensure an adequate sample size. If you need a sample
size n from a population of size x, you should select every x/nth individual for the
sample.
• For example, if you wanted a sample size of 100 from a population of 1000, select
every 1000/100 = 10th member of the sampling frame.

Stratified sampling:
• The target population is divided into suitable, non over lapping subpopulations or
strata. Each stratum should be homogeneous within and heterogeneous between
other strata.
• In a study of stroke outcomes, we may stratify the population by sex, to ensure equal
representation of men and women. The study sample is then obtained by taking equal
sample sizes from each stratum.
• The overall sampling error is reduced.
Clustered sampling:
• Subgroups of the population are used as the sampling unit, rather than individuals.
• The population is divided into subgroups, known as clusters, which are randomly
selected to be included in the study.

In single-stage cluster sampling:
• All members of the chosen clusters are then
included in the study.
In two-stage cluster sampling:
• A selection of individuals from each cluster is
then randomly selected for inclusion.
In a study of schoolchildren, when a list of all
children attending schools in an area is not available.
One would then use a list of schools, and select a
sample of schools from the list. In this case, schools
are the sampling unit or clusters. Once the sample of
schools has been selected, all of the students in the
sampled schools may be surveyed.

Sample Size:
• Ideally, the sample size chosen for a survey should be based on how reliable the final
estimates must be. In practice, usually a trade-off is made between the ideal sample
size and the expected cost of the survey.
• The size of the sample must be sufficient to accomplish the purpose but should not
be larger than necessary, because it will draw resources from other aspects of the
survey process.
• Sample size is determined by the desired confidence level and precision of your
estimates and the variability of the characteristic being measured for the population.
The formula for calculating the sample size needed to estimate a proportion is
discussed in next slide.

n = 𝒛𝟐𝒑𝒒
𝒅𝟐
n = the sample size
z = the standard normal deviate
(1.96 for a 95% confidence level)
d = the level of accuracy desired,
or sampling error
(often set at .05)
p = the proportion of the population having
the characteristic
being measured (if proportion is unknown,
set p = .50, which is maximum variability)
q = the proportion of the population that does
not have the characteristic (i.e., 1- p)

• If the total population from which the sample is to be drawn is less than 10,000, then
the size of the population must also be taken into account.
• Thus, for a population of size 10,000 or greater, n, above, is the final sample size; for
populations less than 10,000, the following adjustment must be made:
nf = n/1+(n/N)
where,
nf = the final sample size, when population is less than 10,000
n = the sample size for populations of 10,000 or more
N = the size of the total population from which the sample is drawn

5. Collect Data (Fieldwork)
Interviewers should be thoroughly trained in the following matters:
• How to locate the selected households or persons must be given.
• How to approach the respondent to assure they agree to be interviewed.
• How to inform the respondent of the anonymity and confidentiality of their participation.
• How to introduce a consent form, if applicable, and obtain a signature
How to administer the questionnaire so that question wording is not changed from one interview
to the next.
• How to define the terms used in the questionnaire, so that all respondents receive the same
explanation of terms.
• How to deal with new situations.
• How to administer the questionnaire.
How to dress for interviewing so the respondent feels at ease in the presence of the interviewer.
• How to review the completed questionnaire after the interview has taken place to check for
accuracy, consistency, and completeness in the field.
• The importance of the information they are gathering, to adhering to the sample design, to finding
the respondent, to minimizing refusals, and of their contribution to the overall survey effort.

6. Train Interviewers
Interviewer training should comprise both classroom and field training.
A day or two of supervised practice interviews in the field can do much
to assure quality data collection when the real fieldwork begins.
When fieldwork is about to begin, the following supplies will be
needed for the interviewers:
• Sufficient supplies of questionnaires, pencils, and pencil sharpeners.
(Pencils are easier to use because of erasures that are often needed
during the interview.)
• Any cards or pictures that may accompany the questionnaire.
• Identification of the interviewer via a letter and/or an ID card.
• A clipboard to make it easier to fill out the questionnaire.
• A copy of the reference manual.
• Maps or instructions on how to locate the respondents.

7. Entering And Editing The Data
• Data entry is a stage of survey work when many errors can occur.
• In past for checking error in data entry error there has been double entry of data.
(data are entered twice by different enterers).
• Then the two sets of data are compared (by computer).
• Double data entry is both costly and time-consuming.
• There are numerous computer programs that accomplish editing of data entry
error concurrent with data entry.

7. Entering And Editing The Data
EPI INFO
• Epi Info is statistical software for epidemiology developed by
Centers for Disease Control and Prevention (CDC) in Atlanta,
Georgia (US).
• It provides for easy data entry form and database construction,
customized data entry experience, and data analyses with
epidemiologic statistics, maps, and graphs for public health
professionals who may lack an information technology background.
• If acceptable entry is made then they move to next question.
• An example of allowable codes may be an age range of 15 to 49 for
a reproductive health survey. If the data entry person attempts to
enter a 52 as the response for age, the computer will not accept it.

8. Analyzing The Data
Statistical Program For Data Analysis:
i. Statistical Analysis System (SAS).
ii. Epi Info.
iii. Statistical Packages for the Social Sciences
(SPSS).
iv. Survey Data Analysis (SUDAAN)

9. Reporting The Results
• The survey should be described in a written report.
• The report should include the survey’s objectives,
methods, results, and your interpretation of the
findings.
 The report serves two purposes:
1. To document the methods used to conduct the
survey.
2. To communicate to decision makers, such as
policy makers, funding sources, and program
managers, the findings of the survey.
• Your description of findings, on the other hand, must
be clear and appropriate for decision makers who
may be neither epidemiologists nor statisticians.

Sources Of Error
• All along the route of survey implementation there are places for error to contaminate the
data.
• While it is not possible to eliminate all error, you must be cognizant of potential error,
must attempt to keep it at a minimum, and when all else fails, be prepared to define the
bias that error may cause in the data.
Coverage
error.
Sampling
error.
Measurement
error.
Error due to
nonresponse.
Data processing
error.

Major Take-
Home Points
• Conducting a successful survey entails scores
of activities, each of which must be carefully
planned and controlled.
• A survey is a key step toward collecting data
on practices and perceptions and can help
identify potential interventions to be tested in a
randomized controlled trial.
Shortcuts To Avoid
• Failure to use probability sampling procedures.
• Failure to pretest to the questionnaire.
• Failure to train the interviewers thoroughly.
• Failure to use adequate quality control
procedures.
PRESENTATION TITLE 35

References of Presentation

Thank you
Course: Veterinary Epidemiology & Public Health
Course Code: EPID – 501
Submitted to: Dr. Munibullah

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