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Mixed Methodology

Mixed Methodology

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Mixed Methodology

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  1. Mixed Methodology Choosing an appropriate research design Dr. Victor Lofgreen Walden University Atlanta Residency, Nov 06

  2. 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.)

  3. Research Paradigms • Logical Positivism • Constructivism

  4. Conflict in Paradigms • Two approaches • Positivist/empiricist • Constructivist/phenomenological

  5. Paradigm to Methods • Positivist paradigm • Quantitative Methods • Constructivist paradigm • Qualitative Methods

  6. 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.

  7. 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.

  8. 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)

  9. 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.

  10. 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

  11. 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.”

  12. Research Cycle Inductive Reasoning Deductive Reasoning

  13. 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

  14. Mixed Model Designs • “Combined the qualitative and quantitative approaches in different phases of the research process.”

  15. Five Mixed Method Designs • Sequential Studies, (Two Phase) • Parallel /Simultaneous • Equivalent Status Designs • Dominant –Less Dominant Studies • Multilevel Designs (Levels of Aggregation)

  16. 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

  17. Triangulation Techniques • Data Triangulation • Investigator Triangulation • Theory Triangulation • Methodological Triangulation

  18. 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

  19. Prototypes Quan___________________Qual Experiment Case Study

  20. Classification of Methods • Type of investigation • Type of Data Collection • Type of analysis or inference

  21. Type of Investigation • Confirmatory • Exploratory

  22. Type of Data Collection • Qualitative • Quantitive • Dimension or Stage of Research

  23. Type of Analysis or Inference • Qualitative • Statistical

  24. Confirmatory Investigation

  25. Pure Quantitative • Data are Quantitative • Analysis is Quantitative • Based on a priori theory or hypothesis

  26. Type 1 Confirmatory • Collect Qualitative Data • Data are quantified • Data are subjected to statistical analysis

  27. Type II Confirmatory • Begins with a priori theory or hypothesis • Qualitative data – Interviews / Observations • Data are analyzed in qualitative form

  28. 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

  29. Exploratory Research

  30. Type III Exploratory • Data are quantitative • No a priori theory of hypothesis • Data are statistically analyzed • Traditional quantitative exploratory study

  31. 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

  32. 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

  33. Pure Qualitative • Data Qualitative • Data Analysis Qualitative • No A Priori Theory or Hypothesis

  34. Multiple Application Designs • Parallel Mixed Models • Sequential Mixed Models

  35. Mixed Model Features • Mix both research hypothesis and research questions • Mixed data collection • Mixed Data Analysis

  36. Type VII Parallel Mixed Model • At least one stage of the research includes qual and quan data • The data are collected and analyzed independently

  37. Data Analysis • Descriptive Methods • Inferential Methods • Univariate vs. Multivariate

  38. Descriptive Measures • Measures of Central Tendency • Mean • Mode • Median

  39. Descriptive Measures • Measures of Variability • Average deviation • Variance • Standard Deviation • Interquartile Range

  40. Descriptive Measures • Measure of Relative Standing • Percentile Rank

  41. Quantitative Data Analysis • Data Analysis Matrix

  42. 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

  43. 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

  44. Inferential Methods Cont. • Compare the means of two or more samples • Compare more than one variable (factorial analysis) • ANOVA Analysis of Variance

  45. Inferential Cont • Comparing means of two or more samples while controlling for an extraneous variable • ANCOVA Analysis of covariance

  46. 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

  47. Measures of Association • Pearson’s R correlation • Chi Square test of Independence

  48. Multivariate Methods • Multiple Regression • Several Independent Variables compared to a single dependent variable • Canonical Correlation • Several independent variables compared to several dependent variables.

  49. 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

  50. Qualitative Data Analysis • Qualitative Typology Matrix