TOPIC EIGHT:SECONDARY DATA

Research Methodology

In this chapter

I. IntroductionII. Categorization and applicationsIII. Secondary data searchIV. Issues with secondary dataV. Secondary data evaluation

I. Introduction

Secondary data: data collected during prior studies.

Including raw data and published summaries.Can combine with primary data for research

purposes.Available throughout various mediums.

II. Categorization and applications

Documentary–written and non-written

Surveys–subtypes include: censuses, regular, ad hoc

Overview of secondary data

Multiple-source secondary data

Documentary , survey, or an amalgam of both

Times series (longitudinal studies)

Cohort studies

Area-based data sets

III. Secondary data search

References in publications (books, journal articles).

Within organisations (unpublished sources).Tertiary source –online indexes and

catalogues. References in published guides (Table 8.1).Data held by organisations and entities.The Internet (Table 8.2).

IV. Issues with secondary data

Advantages Fewer resource requirements

UnobtrusiveLongitudinal studies may be feasible

Provision of comparative and contextual dataUnforeseen discoveries may occurGenerally permanent and available

IV. Issues with secondary data

DisadvantagesPurpose of research may not match the research

needs Access may be difficult or costly

Aggregations and definitions may be unsuitableNo real control over data quality

Initial purpose may affect data presentation

V. Secondary data evaluation

Data resource must:

Enable the research question(s) to be answered

Enable research objectives to be met

Have greater benefits than their associated costs

Allow access for research

V. Secondary data evaluation

Overall suitabilityPrecise suitability, including reliability and

validity - assessment of collection methods

- clear explanation of collection techniques

Measurement validityMeasurement bias and deliberate distortionCoverage and unmeasured variables

- ensure exclusion of unwanted data- ensure sufficient data remain for analysis

Costs and benefits

V. Secondary data evaluation

Response rates & actual sample size required

Actual sample size required:n: minimum (adjusted minimum) sample sizere%: estimated response rateWith 95% confidence interval and 5% margin

of error

Approaches to gaining access

Overcoming organisational concerns

Identifying possible organisational benefits

Appropriate forms of communication

Incremental access

Establishing researcher credibility

Factors in sample size selection

Confidence needed in the data

Margin of error that can be tolerated

Types of analyses to be undertaken

Size of the sample population and distribution

Response rate

Non- respondents and analysis of refusals

Obtaining a representative sample

Calculating the active response rate

Estimating response rate and sample size

Technique for probability sampling

Simple random

Systematic

Stratified random

Cluster

Multi-stage

III. Non-probability sampling

Deciding on a suitable sample size

Selecting the appropriate technique

Non-probability sampling techniques

Quota sampling (larger populations)Purposive samplingSnowball samplingSelf-selection samplingConvenience sampling