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Observational Research. Naturalistic Observation: – Unobtrusive observation (avoid the Hawthorne Effect) Habituation Indirect measures – Count the results.

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Presentation on theme: "Observational Research. Naturalistic Observation: – Unobtrusive observation (avoid the Hawthorne Effect) Habituation Indirect measures – Count the results."— Presentation transcript:

1 Observational Research

2 Naturalistic Observation: – Unobtrusive observation (avoid the Hawthorne Effect) Habituation Indirect measures – Count the results of behavior, use a survey – Disadvantages: time & money – Advantages: ecological validity

3 Observational methods EEthnography: researcher is immersed in the behavioral or social system being studied. Often used by anthropologists (skip pages ) – Decide whether to be a participant or nonparticipant and overtly or covertly – Reactivity might be a problem if overt and ethical issues might surface if using covert method is used – Issues related to gaining access to a setting or group might present

4 Observational Methods Case histories require that you study a single or just a few cases – Case studies are particularly useful when the goals is behavioral change or when organizations are studied (e.g., learning/education/ and industrial/organizational settings)

5 Observational Methods Archival research involves studying existing records such as historical accounts, police records, published articles, or media – Requires a specific and refined hypothesis – Might consider how you will gain access to the data, the completeness of the record (do you need more than one source)

6 Observational Methods Content analysis: involves analyzing verbal written or spoken record for the occurrence of specific categories of events, items, or behavior. – Some overlap with archival research; some people define content analysis as pertaining specifically to language while others have a broader definition. Might include conversations, books, movies, blogs, etc. – Successful content analyses require that researchers be objective and systematic, and have clear operational definition and/or coding schemes. – Consider issues related to sampling (avoid a biased sample) and observer bias (more than one coder)

7 Behavioral Categories & Coding Schemas Behavioral categories operationally define what behaviors are coded during the observation period Clearly defined hypotheses To develop categories you could make preliminary observations, conduct a lit review, or be very specific about your research goals and hypotheses

8 Quantifying Behaviors Frequency method: record the number of times a behavior occurs Duration method: record how long the behavior lasts. Interval method: divide the observation period into time intervals, record the number of times the behavior occurs within each time interval (e.g., verbal exclusion during 2 minute time periods)

9 Recording single events vs. behavioral sequences Behavioral sequence can be thought of – ABCs of the behavior: antecedent, behavior, consequence – Antecedent only or consequence only

10 Consider sampling or recording complex behaviors Time sampling Individual sampling Event sampling: observe only one behavior Record behaviors code later by watching video repeatedly

11 Reliability Interrater reliability: involves using multiple coders – Ensures that observers are accurate – Allows for replication – Allows coders to detect and correct any discrepancies

12 Methods of determining reliability Percent agreement ((total # agreement/total # observation) x 100)); >70% is acceptable Cohens Kappa κ = P o – P c /1– P c – Used for categorical or dichotomous data – where P o = observed proportion of actual agreement, and P c = proportion of expected agreement Pearsons r – can be used with continuous data but it might produce a significant correlation if disagreements are numerous (as long as the magnitudes increase or decrease in a similar fashion) Intraclass correlation coefficient (ICC) – (r I ) should be used for continuous data. This method uses an ANOVA approach (means squares within and between subjects

13 Sources of bias Observer bias: when being aware of the hypothesis influences coding. Can use blind observers Observers interpret rather than record behavior

14 Chi square A non parametric test – chi-square & fishers exact test is distribution free and relies only on frequencies – tests can only be used under certain circumstances chi-squares: dichotomous or categorical data fishers exact: 2 by 2 table or two dichotomous variables.

15 Chi-square To calculate χ 2 determine the frequency of each cell if no differences existed (frequency expected, (ƒe) and then compare this to the actual or observed frequencies (ƒo). – The greater the difference between expected and observed frequencies the more likely it is that differences exist. χ 2 = (ƒo – ƒe) 2 / ƒe Compare χ 2 observed to χ 2 critical in the χ 2 sampling distribution

16 Chi-square To report your findings: χ 2 (df, N = #) = statistic value, p-value χ 2 (1, N = 90) = 0.89, p =.35 Where df = (r-1) x (c-1)


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