Survey research lecture 9

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Advance Research one Survey Research Lecture-9 Muhammad Shafiq, University of Balochistan, Quetta

Transcript of Survey research lecture 9

Page 1: Survey research lecture 9

Advance Research one

Survey ResearchLecture-9

Muhammad Shafiq,

University of Balochistan, Quetta

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1. Basic Definitions for surveys

Survey: a research technique in which information (primary data) is gathered from a sample of people to make generalizations.

Primary data: data gathered and assembled specifically for the project at hand.

Sample of the survey: respondents who are asked to provide information, assuming that they can represent (possess same features with) a target population.

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POPULATION

SAMPLESample: Subset of a larger population

Selecting a Sample

Sampling:• Who is to be sampled?• How large a sample?• How will sample units be selected?

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Basic Definitions for sampling (http://www.stats.gla.ac.uk/steps/glossary/sampling.html)

Target population: the group about which the researcher wishes to draw conclusions and make generalizations

Random sampling: selecting a sample from a larger target population where each respondent is chosen entirely by chance and each member of the population has a known, but possibly non-equal, chance of being included in the sample.

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Basic Definitions for data collection

Surveys ask respondents (who are the subjects of the research) questions by use of a questionnaire.

Respondent: The person who provides information (primary data) by answering a questionnaire or an interviewer’s questions.

Questionnaire: a list of structured questions designed by the researchers for the purpose of codifying and analyzing the respondents’ answers scientifically.

Advantages of Surveys: Quick, Inexpensive, Efficient, Accurate, Flexible way of gathering information.

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2. Errors in Surveys

2.1. Random Sampling Error

2.2. Systematic Error (sample bias)2.2.1. Respondent error

* Nonresponse bias

* Response bias

2.2.2. Administrative error

* Data processing error

* Sample selection error

* Interviewer error

* Interviewer cheating

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2.1. Random Sampling Error

• Even if randomly selected, samples may possess different characteristics than the target population (the likelihood of bias is reduced but still exists)

• This is a statistical fluctuation due to chance variation.

• Then, an important difference occurs between the findings obtained from this sample and the findings obtained from a possible census of the whole target population.

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Continue…• Consider the hypothetic case in which a study

sample could be increased until it was infinitely large; chance variation of the mean, or random error, would be reduced toward zero. These are random errors.

• Systematic errors would not be diminished by increasing sample size.

(Bias in Research Studies, http://radiology.rsna.org/content/238/3/780.full)

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2.2. Systematic Error• Systematic error results from some mistake(s) done

in the design and/or execution of the research.• All types of error -except random sampling error,

are included in this definition,• Sample bias: a persistent tendency for the results

of a sample to deviate in one direction from the true value of the population parameter.

• Sample bias can arise when the intended sample does not adequately reflect the spectrum of characteristics in the target population.

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2.2.1. Respondent Bias

• A classification of sample bias resulting from some respondent action or inaction

• Nonresponse bias• Response bias

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Nonresponse Error

• Nonrespondents: in almost every survey information from a small or large portion of the sample cannot be collected. These are those people who refuse to respond, or who can not be contacted (not-at-homes)

• Self-selection bias: only those people who are interested strongly with topic of the survey may respond while those who are still within the same sample but indeferent or afraid avoid participating.

• This leads to the over-representation of some extreme positions, but under-representation of others.

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Response Bias

• A bias that occurs when respondents tend to answer questions with a certain inclination or viewpoint that consciously (deliberate falsification) or unconsciously (unconscious misinterpretation) misrepresents the truth.

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Reasons of response bias

• Knowingly or unknowingly people who answer questions of the interviewer may feel unconfortable about the truth that they share with others, and change it in their responses.

• They may desire to show themselves as more intelligent, wealthy, sensitive, etc. than they really are.

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Acquiescence bias (positive answers)

Extremity bias (exaggerated answers)

Interviewer bias (answers acceptable by the interviewer)

Auspices bias (answers acceptable by the organization)

Social desirability bias (answers creating a favorable impression)

Types of Response Bias

Deliberate falsification (consciously false answers)

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2.2.2. Administrative Error

• Unadvertently or carelessly improper administration and execution of the research task

• Blunders are:• Confusion• Neglect• Omission

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Types of Administrative ErrorsData processing error: incorrect data entry, computer

programming, or other procedural errors during the analysis stage.

Sample selection error: improper sample design (e.g. based on incomplete databases) or sampling procedure execution (e.g. executed in daytime while most of the target population are working)

Interviewer error: mistakes done by the interviewer (e.g. taking wrong or incomplete notes about the answers of the respondents.

Interviewer cheating: filling in fake or false answers indeed not given by the respondents.

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3. Classification of Survey Methods

3.1. Structure of the questionnaire:

* whether standardized questions with a limited number of allowable answer -multiple choices

* or unstandardized open ended questions with the possibility of being answered in numerious ways.

3.2. Level of Directness of the questions:

* whether direct/undisguised questions

* or indirect/disguised questions to hide the real purpose of the survey

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Classification of Survey Methods

3.3. Time basis of the Survey:Cross-Sectional Study: data on various segments of a

target population are collected at a single moment in time to make comparisons among segments.

Longitudinal Study: data are collected at different times from the similar respondents to compare trends and identify changes.

Panel Study: A longitudinal survey of exactly the same respondents to record (in a diary) their attitudes, behaviors, or purchasing habits over time.