STRATEGIES IN QUANTITATIVE DATA COLLECTION

Steps in the Process of Data Collection :

1.Determining the participant to study

2.Obtaining permission needed from several individuals and organization

3.Considering what types of information to collect from several sources, available to the quantitative research

4.Locating and selecting instrument to use

5.Administering the data collection process to collect data

Population and Sample

Population : a group of individual who have the same characteristics

Sample : a subgroup of the target population that the researcher plans to study for generalizing about the target population.

1 Probability Sampling: the researcher selects individual from the population who are representative of that population

a. Simple random sampling : the researcher selects participant for the sample so that any individual has an equal probability of being selected from the population.

b. Systematic sampling : the researcher choose every nth individual or site in the population until the researchers reaches the desired sample size

c. Stratified sampling : the researcher divides (stratify) the population on some specific characteristic and then using simple random sampling, sampling from population.

d. Multistage cluster sampling : the researcher chooses a sample in two or more stages because either the researcher cannot easily identify the population is extremely large

2. Non Probability Sampling: the researcher selects individuals because they are available, convenient, and represent some characteristic the investigator seeks to study.

a. Convenience sampling : the researcher selects participant because they are willing and available to be studied.

b. Snowball sampling : the researcher asks participants to identify others to become members of

sample size : the larger the sample the less the potential error is that the sample will be different from the population.

What permission will the researcher need ?

1.The purpose of the study

2.The amount of time the researcher will be at the site collecting data

3.The time required of participants

4.How the researcher will use the data or result

5.State specific activities that will be conducted

6.The benefits to the organization or the individual because of the study.

Reliability and Validity

Reliability means that scores from an instrument are stable and consistent. Scores should be nearly the same when researchers administer the instrument multiple times at different times. Also, scores need to be consistent. When an individual answers certain questions one way, the individual should consistently answer closely related questions in the same way.

Validity is the development of sound evidence to demonstrate that the test interpretation (of scores about the concept or construct that the test is assumed to measure) matches its proposed use.

Types of Reliability

No	Form of Reliability	Number of Times Instrument Administered	Number of Different Versions of the Instrument	Number of Individuals Who Provide Information
1	Test–retest reliability	Twice at different time intervals	One version of the instrument	Each participant in the study completes the instrument twice.
2	Alternate forms reliability	Each instrument administered once	Two different versions of the same concept or variable	Each participant in the study completes each instrument.
3	Alternate forms and test– retest reliability	Twice at different time intervals	Two different versions of the same concept or variable	Each participant in the study completes each instrument.
4	Interrater reliability	Instrument administered once	One version of the instrument	More than one individual observes behavior of the participants.
5	Internal consistency reliability	Instrument administered once	One version of the instrument	Each participant in the study completes the instrument .

Sources of Validity Evidence and Examples

No	Validity Evidence	Types of Tests or Instruments to Which Validity Evidence Is Applicable	Type of Evidence Sought	Examples of Evidence
1	Evidence based on test content	Achievement tests, credentialing tests, and employment tests	Evidence of an analysis of the test’s content (e.g., themes, wording, format) and the construct it is intended to measure	• Examine logical or empirical evidence (e.g., syllabi, textbooks, teachers’ lesson plans) • Have experts in the area judge
2	Evidence based on response processes	Tests that assess cognitive processes, rate behaviors, and require observations	Evidence of the fi t between the construct and how individuals taking the test actually performed	• Interviews with individuals taking tests to report what they experienced/were thinking • Interviews or other data with observers to determine if they are all responding to the same stimulus in the same way
3	Evidence based on internal structure	Applicable to all tests	Evidence of the relationship among test items, test parts, and the dimensions of the test	• Statistical analysis to determine if factor structure (scales) relates to theory, correlation of items
4	Evidence based on relations to other variables	Applicable to all tests	Evidence of the relationship of test scores to variables external to the test	• Correlations of scores with tests measuring the same or different constructs (convergent/discriminant validity) • Correlations with scores and some external criterion (e.g., performance assessment—test-criterion validity) • Correlations of tests scores and their prediction of a criterion based on cumulative databases (called meta analysis— validity generalization)
5	Evidence based on the consequences of testing	Applicable to all tests	Evidence of the intended and unintended consequences of the test	• Benefits of the test for positive treatments for therapy, for placement of workers in suitable jobs, for prevention of unqualified individuals from entering a profession, for improvement of classroom instructional practices, and so forth

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