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Mixed Methodology. Choosing an appropriate research design Dr. Victor Lofgreen Walden University Atlanta Residency, Nov 06. Logical Positivism. Ontology (Nature of reality) There is a single reality.

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mixed methodology

Mixed Methodology

Choosing an appropriate research design

Dr. Victor Lofgreen

Walden University

Atlanta Residency, Nov 06

logical positivism
Logical Positivism

Ontology (Nature of reality) There is a single reality.

Epistemology (relationship of the knower to the known) The knower and the known are independent

Axiology (role of values in inquiry) Inquiry is value free

Generalizations: Time and context free generalizations are possible.

Causal Linkages: There are real causes that are temporally precedent or simultaneous with effects.

Deductive Logical: Emphasis on arguing from the general to the specific, or a particular emphasis on a priori hypotheses testing (or theory.)

research paradigms
Research Paradigms
  • Logical Positivism
  • Constructivism
conflict in paradigms
Conflict in Paradigms
  • Two approaches
    • Positivist/empiricist
    • Constructivist/phenomenological
paradigm to methods
Paradigm to Methods
  • Positivist paradigm
    • Quantitative Methods
  • Constructivist paradigm
    • Qualitative Methods
constructivist
Constructivist
  • Ontology (Nature of reality. There are multiple, constructed realities.
  • Epistemology (relationship of the knower to the known) The knower and the known are inseparable.
  • Axiology (role of values in inquiry) Inquiry is value-bound
  • Generalizations: Time and context free generalizations are not possible.
  • Causal Linkages: It is impossible to distinguish causes from effects
  • Inductive Logic: Emphasis on arguing from the :particular to the general, there is emphasis on “grounded” Theory.
post positivist position
Post Positivist Position
  • Value-ladenness of inquiry: Research is influenced by the values of investigators.
  • Theory-ladenness of the facts: Research is influenced by the theory or hypothesis or framework that the researcher uses.
  • Nature of reality: Our understanding of reality is constructed.
the evolution of methodological approaches
The Evolution of Methodological Approaches

Period 1 The Monomethod or “Purist” Era

  • The purely Quantitative Orientation
    • Single Data Source (QUAN)
    • Within one paradigm/Model, multiple data sources
    • Sequential (QUAN/QUAN)
    • Parallel Simultaneous (QUAN+QUAN)
  • The Purely Qualitative Orientation
    • Single Source (QUAL)
    • Within one paradigm/Model, Multiple Data Sources
    • Sequential (QUAL/QUAL)
    • Parallel/Simultaneous (QUAL+QUAL)
controversy ontology and causality
ControversyOntology and Causality
  • Naïve Realism – Objective External Reality
  • Critical Realism – Objective Reality known approximately or probabilistically.
  • Transcendental Realism – Social phenomena exist in an objective world. There are some stable lawful relationships.
  • Ontological Relativism: There are multiple social realities that are parts of human intellect and that may change as their constructors change.
causal relationships from ontological distinctions
Causal Relationships from Ontological Distinctions
  • Post positivists believe in the proportional view of the truth
  • Pragmatists believe there may be causal relationships but we may never be able to pin them down.
  • Constructivists believe that all entities are simultaneously shaping each other
pragmatism and the choice of strategy
Pragmatism and the Choice of Strategy
  • “Pragmatists consider the research question to be more important than the either the method or the world view that is supposed to underlie the method.”
research cycle
Research Cycle

Inductive

Reasoning

Deductive Reasoning

paradigm comparison
Paradigm Comparison

Paradigm

Positivism

Post positivism

Pragmatism

Constructivism

Quantitive

Primarily Quantitative

Quan + Qual

Qualitative

Logic

Deductive

Primarily Deductive

Deductive + Inductive

Inductive

Epistemology

Objective Dualistic

Modified Dualistic

Both Obj & Sub

Subjective

Axiology

Value Free

Values may be controlled

Values Considered Chose the results that fit best

Value Bound

Ontology

Naïve Realism

Critical Transcendental

Ext Reality – Best Out

Relativism

Causal Linkages

Real Causes temporally precedent to or simulations with effects

Some lawful stable relationships . Causes are probabilistic and change over time

There may be causal relationships but we may never know them.

Everything is simulations shaping everything else – Can’t distinguish difference between causes and effects

mixed model designs
Mixed Model Designs
  • “Combined the qualitative and quantitative approaches in different phases of the research process.”
five mixed method designs
Five Mixed Method Designs
  • Sequential Studies, (Two Phase)
  • Parallel /Simultaneous
  • Equivalent Status Designs
  • Dominant –Less Dominant Studies
  • Multilevel Designs (Levels of Aggregation)
maxmincon principle
MAXMINCON Principle
  • Maximize the experimental variance to allow enough difference between groups to allow the effect to occur.
  • Minimize the error variance provides power for detecting the difference between groups. Take out the noise to better detect the signal. Error variance comes from random fluctuations, in reactions, behaviors, an/or measurements.
  • Control of extraneous variables – remove all competing variables
triangulation techniques
Triangulation Techniques
  • Data Triangulation
  • Investigator Triangulation
  • Theory Triangulation
  • Methodological Triangulation
taxonomy of data collection

Data Collection Technique

Setting

Manipulation

Orientation

Controlled

Natural

Yes

No

Confirmatory

Exploratory

Lab Experiment

X

X

X

Single-Subject Study

X

X

X

Field Experiment

X

X

X

Survey Study

X

X

X

Relationship Studies

X

X

X

Prediction Studies

X

X

X

Archival studies

X

X

Causal-comparative

X

X

X

Historical Research

X

X

X

X

Case/Field Study

X

X

X

X

Descriptive Research

X

X

X

Developmental Research*

X

X

X

X

Taxonomy of Data Collection
prototypes
Prototypes

Quan___________________Qual

Experiment Case Study

classification of methods
Classification of Methods
  • Type of investigation
  • Type of Data Collection
  • Type of analysis or inference
type of investigation
Type of Investigation
  • Confirmatory
  • Exploratory
type of data collection
Type of Data Collection
  • Qualitative
  • Quantitive
  • Dimension or Stage of Research
type of analysis or inference
Type of Analysis or Inference
  • Qualitative
  • Statistical
pure quantitative
Pure Quantitative
  • Data are Quantitative
  • Analysis is Quantitative
  • Based on a priori theory or hypothesis
type 1 confirmatory
Type 1 Confirmatory
  • Collect Qualitative Data
  • Data are quantified
  • Data are subjected to statistical analysis
type ii confirmatory
Type II Confirmatory
  • Begins with a priori theory or hypothesis
  • Qualitative data – Interviews / Observations
  • Data are analyzed in qualitative form
type v confirmatory
Type V Confirmatory
  • Data are Quantitative
  • Data are reclassified into qualitative form
  • Data are analyzed to generate profiles and categories.
  • The results are then used for further research
type iii exploratory
Type III Exploratory
  • Data are quantitative
  • No a priori theory of hypothesis
  • Data are statistically analyzed
  • Traditional quantitative exploratory study
type iv exploratory
Type IV Exploratory
  • Data are Qualitative
    • Sentence Completion
    • Story telling
  • Data are converted to Quantitive form
  • Data are subjected to statistical analysis
    • Nonparametric
    • Log linear modeling
    • Logistic regression
type vi exploratory
Type VI Exploratory
  • Data are Quantitative
  • Data converted to Qualitative
    • Profiles or Group Identities
  • Data Analyzed as Qualitative
    • Results are used to build models or determine prototypes
pure qualitative
Pure Qualitative
  • Data Qualitative
  • Data Analysis Qualitative
  • No A Priori Theory or Hypothesis
multiple application designs
Multiple Application Designs
  • Parallel Mixed Models
  • Sequential Mixed Models
mixed model features
Mixed Model Features
  • Mix both research hypothesis and research questions
  • Mixed data collection
  • Mixed Data Analysis
type vii parallel mixed model
Type VII Parallel Mixed Model
  • At least one stage of the research includes qual and quan data
  • The data are collected and analyzed independently
data analysis
Data Analysis
  • Descriptive Methods
  • Inferential Methods
  • Univariate vs. Multivariate
descriptive measures
Descriptive Measures
  • Measures of Central Tendency
    • Mean
    • Mode
    • Median
descriptive measures39
Descriptive Measures
  • Measures of Variability
    • Average deviation
    • Variance
    • Standard Deviation
    • Interquartile Range
descriptive measures40
Descriptive Measures
  • Measure of Relative Standing
    • Percentile Rank
quantitative data analysis
Quantitative Data Analysis
  • Data Analysis Matrix
type viii sequential mixed model
Type VIII Sequential Mixed Model
  • Data are collected in phases
  • Each phase emphasizes one type of data
  • Data are analyzed and results support the next phase
  • Final results include variety of results
inferential methods tests difference between group means
Inferential MethodsTests difference between group means
  • Compare a group mean with a population mean Z score
  • Compare the means of two samples
    • Independent observation – T Test
    • Non-independent – T Test for Non-independent measures
inferential methods cont
Inferential Methods Cont.
  • Compare the means of two or more samples
  • Compare more than one variable (factorial analysis)
    • ANOVA Analysis of Variance
inferential cont
Inferential Cont
  • Comparing means of two or more samples while controlling for an extraneous variable
    • ANCOVA Analysis of covariance
inferential methods cont46
Inferential methods Cont.
  • Correlation Coefficients not 0
    • T-Test for significance of Pearson’s r
    • F-Test for significance of multiple correlation
    • T-test or F-test for significance of slope in multiple regression analysis
measures of association
Measures of Association
  • Pearson’s R correlation
  • Chi Square test of Independence
multivariate methods
Multivariate Methods
  • Multiple Regression
    • Several Independent Variables compared to a single dependent variable
  • Canonical Correlation
    • Several independent variables compared to several dependent variables.
multivariate analysis cont
Multivariate Analysis Cont
  • Discriminate Function Analysis
    • To find a set of variables that differentiate two or more groups
  • Factor Analysis
    • Explanatory – to find underlying constructs of a set of variables
    • Confirmatory – find the predicted construct of a set of variables
qualitative data analysis
Qualitative Data Analysis
  • Qualitative Typology Matrix
mixed data analysis strategies
Mixed Data Analysis Strategies
  • Data Transformation
    • conversion from one type to another
  • Typology development:
    • Analysis of one type yields a typology that is use by the other method.
  • Extreme-case analysis:
    • Identify extreme cases for data collection from another method
  • Data consolidation/merging:
    • Joint review to create or consolidate variables or data sets for further analysis
the end
The End

Victor Lofgreen, PhD

Walden University

Atlanta Residency

Nov. 2006

Reference:

Tashakkori, A & Teddlie, C, 1998, Mixed Methodology Combining Qualitative and Quantitative Approaches, Thousand Oaks, CA, Sage Publications