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Quantitative Research SPED 500 Dr. Sandra Beyda Designs that maximize objectivity by using numbers, statistics, structure, and experimenter control Modes.

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Presentation on theme: "Quantitative Research SPED 500 Dr. Sandra Beyda Designs that maximize objectivity by using numbers, statistics, structure, and experimenter control Modes."— Presentation transcript:

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2 Quantitative Research SPED 500 Dr. Sandra Beyda

3 Designs that maximize objectivity by using numbers, statistics, structure, and experimenter control Modes –Experimental mode –Non-experimental mode

4 Structure of a Data Based Study Abstract Introduction Method Results Discussion Summary & Conclusions References

5 The Abstract Provides an accurate overview Is concise and specific Contains fewer than 120 words Includes: –Topic/problem, in one sentence –Participants –Method used –Summary of the important findings –Conclusions and implications

6 Introduction Presents the specific problem under study Describes the research strategy Reviews earlier work related to the problem States a hypothesis and/or research question(s)

7 Method Detailed description of study Enough information for a reader to replicate the study. –Who participated in study –What materials were needed –What data were collected –What were participants required to do

8 Results Summarizes data collected and statistical analysis used Includes statistical design Includes all relevant results May include tables and figures

9 Discussion Includes statement of the support or nonsupport for original hypothesis Comments on the meaning of the results Explains the results in regard to the central purpose of the study Discusses inconsistencies in findings compared to past research Comments on the importance of the study

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11 True experiment Quasi- experimental Single Subject

12 True Experiments Internal validity External validity –Randomization –Systematically vary or manipulate –Hold constant –Assume invariance or irrelevance –Matching –Statistical control

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14 Threats to Internal Validity When there is a statistically significant result (X > Control) History Maturation Testing Nonequivalence Regression Mortality Interactions with Selection Instrumentation

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16 Threats to Internal Validity When there are non-significantly different results: Small sample size Treatment implementation Insensitive dependent variable John Henry Effect Treatment not long enough Treatment diffusion

17 Threats to External Validity Population validity Ecological validity Operations validity

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20 Posttest only Pretest-Posttest Solomon 4 Group Design Factorial Design

21 No Random Assignment! One group Time series approach Two groups Static group comparison Non-equivalent control group

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23 Reliable measurements Repeated measurements Baseline Introduction of treatment Reversal or withdrawal Maintenance Replication

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25 Single Subject Research Designs AB ABA ABAB Multiple Baseline

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27 How about a little practice exercise?

28 Don’t worry. I’ll wait!

29 How about marital bliss?

30 Descriptive Comparative Correlational Ex Post Facto

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32 Descriptive Research Single Group Cross-sectional Longitudinal

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34 Comparative Research

35 Correlational Research Purpose: What is the relationship between variable A and B? Uses: –T–Theory building –E–Establish predictive relationships

36 Bivariate correlational studies Prediction studies –Predictor variable –Criterion variable

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40 Correlational Research Limitations Correlation and Causation Spurious Correlations Size of Correlation Coefficients

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43 Purpose: –To examine how an identified independent variable effects the dependent variable when circumstances do not allow for the manipulation of the independent variable Conditions for establishing cause-effect connections –( 1) statistical significance- –(2) IV before DV. –(3) Alternative causes

44 Ex-Post Facto Research Designs Single Group Between Group Problems –Self selection –Correlation-causation fallacy –Direction of causality

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