6301 wk4assgn

Quantitative & Qualitative Research – Overview

SOCW 6301

Quantitative vs. Qualitative Design Usual Distinctions …

Quantitative AND Qualitative Design Potential Combined Uses …

Quantitative VERSUS Qualitative Design Common Techniques …

Distinctions Obvious: Distinction between numbers and words

numerical narrative Distinction in purpose

hypothesis creating testing

meaning and/or theory

Distinction in overarching paradigm deductive inductive positivist naturalist

Distinctions  Less obvious: Distinction according to theoretical issues The value of the types of data The relative scientific rigor of the data Basic underlying philosophies of research/evaluation

Distinction according to practical issues Validity / credibility of findings Staff skill Costs Time constraints

Theoretical Issues – Value of types of data

 Trade-off between … Quantitative Qualitative breadth depth

generalizability in-depth understanding

Example:

Theoretical Issues – Scientific rigor

 Trade-off between … Quantitative Qualitative objective contextual accurate participant recall sophisticated stats analysis of large

amounts of descriptive data

NOTE: Today we recognize that the two types of design are often synergistic; therefore we combine them in a mixed methods design

Theoretical Issues – Phil. Foundation

 Trade-off between … Quantitative Qualitative one reality multiple realities objective truth truth is constructed independence person-in-environment

Practical Issues – Validity / Credibility Studies are designed for various

audiences Funding agencies Policymakers in governmental and private

agencies Project staff and clients Other "stakeholders"

Practical Issues – Validity / Credibility Skepticism regarding a study’s outcomes May reject qualitative methodology as

unsound or weak for a specific case Favor quantitative information Accustomed to basing funding decisions on

numbers and statistical indicators BUT: May also be suspicious of statistics

and "number crunching" Consider richer data from qualitative research

more trustworthy and informative

Practical Issues – Staff skills Qualitative methods require good staff

skills Considerable supervision to yield

trustworthy data In-depth interviewing Observations Focus groups

Practical Issues – Staff skills  Some quantitative research methods can be

mastered easily with the help of simple training manuals Small-scale, self-administered questionnaires Most questions can be answered by yes/no

checkmarks or selecting numbers on a simple scale NOTE: Large-scale, complex surveys usually

require more skilled personnel to design the instruments and to manage data collection and analysis

Practical Issues – Costs  Difficult to generalize about the relative costs of the

two methods  Amount of information needed  Quality standards followed for the data collection  Number of cases required for reliability and validity

 Short survey based on a small number of cases (25-50) and consisting of a few "easy" questions would be inexpensive  Would provide only limited data

 Focus group session for a subset of the 25-50 respondents might be even cheaper  Could provide more "interesting" data  BUT: Data would be primarily useful for generating new hypotheses

to be tested by more appropriate qualitative or quantitative methods  To obtain robust findings, the cost of data collection is

bound to be high regardless of method

Practical Issues – Time constraints Data complexity and quality affect the

time needed for data collection and analysis A good survey requires considerable time

to create and pretest questions and to obtain high response rates Qualitative methods may be even more

time consuming Data collection and data analysis overlap Process encourages the exploration of new

evaluation questions

Practical Issues – Time constraints  If insufficient time is allowed for the

study, it may be necessary to curtail the amount of data to be collected or to cut short the analytic process  In severe time constraints - for example,

where budgetary decisions depend on the findings - the choice of the best method can present a serious dilemma

Mixed Methods Designs Mixed Methods Design – a design that

includes studies that “uses mixed data (numerical and text) and alternative tools (statistics and text analysis) … in other words, the design includes both QUALITATIVE and QUANTITATIVE data collection and analysis

Mixed Methods Designs Mixed Methods Design Parallel form (concurrent mixed method

design) – both types of data are collected and analyzed

Sequential form (sequential mixed method design) – one type of data provides a basis for collection of another type of data

Sequential form (conversion mixed method design) – one type of data are converted (either qualitized or quantitized) and analyzed again

Mixed Methods Designs