Observational Research

Observational Research 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

Observational methods EEthnography: researcher is immersed in the behavioral or social system being studied. Often used by anthropologists (skip pages 239-242) 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

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)

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)

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)

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 help refine your categorical codes (the behaviors that you will record)

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)

Recording single events vs. behavioral sequences Behavioral sequence can be thought of ABC’s of the behavior: antecedent, behavior, consequence Antecedent only or consequence only

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

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

Methods of determining reliability Percent agreement ((total # agreement/total # observation) x 100)); >70% is acceptable Cohen’s Kappa κ = Po – Pc/1– Pc Used for categorical or dichotomous data where P o = observed proportion of actual agreement, and Pc = proportion of expected agreement Pearson’s 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) (rI) should be used for continuous data. This method uses an ANOVA approach (means squares within and between subjects

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

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

Chi-square To calculate χ2 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. χ2 = ∑ (ƒo – ƒe)2/ ƒe Compare χ2 observed to χ2 critical in the χ2 sampling distribution

Chi-square To report your findings: χ2(df, N = #) = statistic value, p-value χ2(1, N = 90) = 0.89, p = .35 Where df = (r-1) x (c-1)