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by: Spencer Smitham


Spencer Smitham
GPA 3.97


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Class Notes
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This 10 page Class Notes was uploaded by Spencer Smitham on Saturday September 12, 2015. The Class Notes belongs to PSYC 3980 at University of Georgia taught by Staff in Fall. Since its upload, it has received 11 views. For similar materials see /class/202469/psyc-3980-university-of-georgia in Psychlogy at University of Georgia.




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Date Created: 09/12/15
Psyc 3980 Final study guide Chapter 8 Quasiexperimental design Often we cannot manipulate a variable ofinterest Quasiindependent variables Subject variable individual characteristic used to select participants to groups Natural treatment exposure in the quotreal world defines how participants are selected Types of Quasiexperimental designs Nonequivalentcontrolgroup designs Experimental and comparison groups that are designated before the treatment occurs and are not created by random assignment Beforeandafter designs Pretest and posttest but no comparison group Nonequivalent control group designs Random assignment cannot be used to create groups Confounds related to equivalency of groups cannot be eliminated Often high in external validity Particularly ecological validity Matching Individual matching individual cases in the treatment group are matched with similar individuals Aggregate matching identifying a comparison group that matches the treatment group in the aggregate rather than trying to match individual cases Regression to the mean can be a problem Before and After designs Useful for studies of interventions that are experienced by virtually every case in some population No comparison group Fixedsample panel design one pretest and one posttest Interruptedtimeseries design examine observations before and after a naturally occurring treatment Multiple group beforeandafter design several beforeandafter comparisons are made involving the same independent and dependent variables but with different groups Repeatedmeasures panel designs include several pretest and posttest observations Memories of 911 Participants viewed word cues while in fMRI scanner Words belonged to one of two categories Sept 2001 and summer 2001 Participants also rated the word cues on a number of dimensions Participants were divided into groups near the World Trade Center or far from the WTC ex postfacto Negative correlation between distance and memory rating near yielded higher memory ratings Researchers also found a different pattern ofbrain activity between the near and far groups Memories of 911quasieXperimental characteristics Summer condition served as a control condition Baseline for comparison 911 is a natural treatment Researchers could not manipulate Random assignment was not possible Participants did not decide on their treatment condition Culture and Cognition Can a bicultural individual be experimentally induced to switch his her cultural mental set Randomly assigned to priming condition to activate mental sets American Chinese Participant rated the internal eXternal forces on the behavior of a fish Participants were selected based on biculturalism But randomly assigned to priming conditions Crosssectional designs Selects groups ofpeople of different ages and then compares these age groups on psychological processes Confounded by Cohort effects Period effects Longitudinal designs Same research participants are followed over time Problems Attrition Secular trends Crosssequential designs Timelag design a researcher aims to determine the effects of time of testing while holding age constant Crosssequential design tests two or more age groups at two or more time periods Avoids problems of both crosssectional and longitudinal designs NoneXperiments Researcher has even less control over the independent variable and seldom can specific levels of the independent variable be precisely established or quantified Serious limitations in terms ofinternal validity EX post facto control group design Experimental and comparison groups that are not created by random assignment Individuals may decide whether to enter the treatment or control group Selection bias is a significant issue Chapter 9 Small N and Single Subject Designs Small N designs Alternative to group designs Generally involve between 19 participants Systematic procedure for testing changes in a single subject s or small number of subjects behavior Often used in clinical cases Components of smallN designs 1Repeated measurement of the dependent variable prreintervention measurements cannot be taken retrospective data may be used 2Baseline phase A Intervention not offered to subject Acts in place ofa quotcontrol group Repeated measurements of the DV are taken until a pattern emerges 3Treatment phases B Intervention is implemented Repeated measurements of the DV are taken Should be as long as the baseline phase 4Graphic display Facilitates monitoring and evaluating the impact of the intervention Types of Patterns Stable line Changes easily detected Generally few problems with the measure Trend Scores increase or decrease over time May even be cyclical No Pattern Possible problems with reliability of measure or client reports Internal validity considerations Repeated measures during the baseline phase help rule out threats to validity Validity threats should appear in the baseline Will not control for an extraneous event history that occurs between the last baseline measurement and the first intervention measurement Measuring targets ofintervention DV should be the target of the intervention Can be measured simultaneously or sequentially Measures ofbehavior are often categorized according to 1Frequency how often behavior occurs 2Duration how long behavior lasts 3Interval time between episodes 4Magnitude intensity of behavioral event Consider who will collect the data Choose nonreactive measures Ensure the measurement process is feasible Consider the measurement s sensitivity Note that target of the measurement must occur relatively frequently Analyzing Small N Designs Common techniques Visual examination of the graph Statistical technique Assessing practical clinical significance is ofprimary importance Determining practical significance Set criteria for success with individual or community Use clinical cutoff scores Weigh costs and benefits of producing the change Visual Analysis Guiding concepts 1Level magnitude of the target variable typically used when the observations fall along relatively stable lines 2Trend direction in the pattern of the data points 3Variability how different or divergent the scores are within a baseline or intervention phase Basic Design Baseline phase A with repeated measurements and an intervention phase B continuing the same measures Fluctuations are difficult to interpret Cannot rule out other extraneous events so causality cannot be established Withdrawal designs Intervention is concluded or is temporarily stopped during the study May pose ethical issues Carryover effects may limit usefulness ABA Design Includes posttreatment followup Followup period should include multiple measures ABAB Design Adds second intervention phase that is identical to the first Replication of treatment phase reduces the possibility that an event or history explains the change Multiple Baseline designs Adds additional subjects target problems or settings to the study Controls for the effects of history Concurrent multiple baseline design Series ofAB designs are implemented at the same time for at least three cases Length of the baseline phase is staggered May have problem finding available subjects Nonconcurrent multiple baseline design Different lengths of time for the baseline period Subjects are randomly assigned to one of the baseline phases Alternatively can be used across different target problems or settings Multiple Treatment designs Nature of the intervention changes over time Each change represents a new phase Yields a more convincing picture of the effect of the treatment program Can change Intensity of the intervention Number of treatments Nature of the intervention Problems of Interpretation Widely discrepant scores in the baseline Delayed changes in the intervention phase Improvement in the target problem scores during the baseline phase Act of graphing can create visual distortions Statistical Analysis Can help avoid the problems associated with visual inspection Requirements of the statistical test may be difficult or impossible to meet in a smallN design Generalizability Difficult to demonstrate in smallN designs Requires replication Direct replication same study with different clients Systematic replication same interventions in different settings Clinical replication combining different interventions into a clinical package to treat multiple problems Chapter 10 Quantitative Analysis Case Study Dun 2008 Can you buy happiness Participants randomly assigned to Money condition 5 or 20 Spending condition self or others 2 X 2 betweensubjects factorial design Types of Statistics Descriptive describe variables in a study Inferential estimate characteristics of a population from a random sample Is the effect we observed due to chance alone Used to test hypotheses about the relationship between variables Must consider level of measurement Frequency Distributions Shows the number of cases andor the percentage of cases who receive each possible score on a variable Often the first step in statistical analysis Grouping values in frequency distributions May group the values if There are more than 1520 It would clarify the distribution Resulting categories Should be logical Should be mutually exclusive and exhaustive Descriptive Statistics Three key features ofa distribution s shape Central tendency Variability Skewness Measures of central tendency Mode probability average Most frequent score May be more than one May fall far from the main clustering of cases in a distribution Median position average Point that divides the distribution in half Cannot be used at the nominal level Mean arithmetic average Sum numbers and divide by N Cannot be used at the nominal level and sometimes not at the ordinal level Mean vs Median Should consider the purpose of the statistic Median often makes more sense at the ordinal level Median is better for skewed distributions Variability Range High score low score Drastically in uenced by one high or low score Variance Average squared deviation of each case from the mean Standard Deviation Square root of the variance Sampling Distributions Distribution of statistics representing all possible samples drawn from a population ofa set size Mean is the same as the population mean Standard error of the mean degree to which the means of the samples vary from the population mean Inferential statistics Confidence that the mean ofa random sample from a population is within a certain range of the population mean Calculating confidence limits 1Calculate the standard error 2Decide on a degree of confidence 3Multiply the standard error by 196 4Add and subtract the value in step 3 from the sample mean Can be used to estimate a population parameter from a sample statistic Can also be used to test a hypothesis Two of the most common hypothesis tests ttest Ftest Statistics to test hypotheses Research vs Null hypothesis Null Hypothesis Prediction that there will be no meaningful difference in the dependent measure across groups Alpha 1 level Conventionally set at 05 or 01 for statistical significance 0L 08 is sometimes used for quotmarginalquot significance Type I and Type 11 error Type I error Rejecting the null when it is true Probability equal to the significance level Equal to alpha Wrongly convict innocent person ofbeing guilty Wrongfully rejected Type 11 error probability equal to B Failing to reject the null when it is false Too stringent of a significance level Too small ofa sample A very small effect Fails to convict guilty person and states they are innocent Wrongfully accepted Inferential Statistics T Test Comparison of group means Comparison of sample mean to known population mean FTest For comparisons when there are two or more independent variables For comparisons when there are three or more conditions Chi Square Often used to test hypotheses involving two categorical variables Determines the likelihood of observed group difference when there was actually no difference in the population Compares observed values to those expected by chance Correlation r Measures relationship between two quantitative variables Range 1 to 1 Positive value variables increase together Negative value as one variable increases the other decreases Value of number indicates strength of relationship Significant correlation indicates it was unlikely due to chance alone Ethics of Statistical Testing Reports should indicate central tendency and variability Abnormalities in distribution shape should be reported Include appropriate graph elements Group data carefully EXplore a prior hypothesis first and be aware that post hoc analysis carries greater risk of error Chapter 11 Qualitative Methods Qualitative Methods Learn about human behavior by listening to people or observing behavior in a natural setting Features of Qualitative Methods Collection of qualitative data As quotexperienced by subject EXploratory research questions Commitment to inductive reasoning Focus on previously unstudied processes and unanticipated phenomena Focus on human subjectivity Meanings that participants attach to events Re eXive research design Design develops as the research progresses Sensitivity to the researcher s subjectivity Qualitative Methods 1Qualitative interviewing Openended relatively unstructured questioning 2Participant observation Sustained relationship with participant during normal daily activities 3Focus groups Unstructured group interviews Qualitative Interviewing Relies on openended questions Follows a preplanned outline of topics instead of fixed questions and response options Researcher engaged more actively in the interview Often longer than structured interviews A quotconversation with a purpose Interviewee Selection Random selection rarely used Interviewees should be Knowledgeable about the subject Open to talking Representative of the range of perspectives Selection should continue until saturation point New interviews seem to yield little additional information Questions and Answers Questions planned around an outline Questions should be short and clear Followup questions are tailored to participant answers Interviewer should try to develop a rapport with the interviewee Participant Observation Social processes are studied as they happen and are left relatively undisturbed Attempts to avoid the artificiality of other designs Considers the conteXt of the behavior Uses participant observers Balance between observing and participating Balance may change over course of study Possible reactive effects Can create boundary issues Observer can note effect on others in the setting and the effect of others on observations Participant Observation process Participant observer must dress and act appropriately given the environment May require introductions Observer must manage relationships carefully Observer must take careful notes Lengthy process Advice for maintaining relationship in the field Develop an explanation for yourself Maintain the support of key figures Be unobtrusive Don t be too aggressive in questioning Ask sensitive questions Be selfrevealing Don t fake social similarity Avoid gift giving Be prepared for difficulty between groups Note taking guidelines 1Describe the context Including the physical setting 2Describe the participants 3Describe the observer 4Describe the actions ofparticipants Including both verbal and nonverbal behavior 5Consider alternative interpretations of the situation 6Explore your feelings in being an observer Considerations for managing relationships Think about how you want to relate to the potential subjects Consider the problems that might rise and how will you might respond Keep in touch with others outside of the research setting Maintain standards of conduct that make you comfortable Systematic Observation Observations made in a more systematic quantitative way Allows comparisons and more confident generalizations Researcher develops standard form on which to record observations Records can be obtained from a random sample ofplaces or times Focus Group Groups of710 unrelated people Led in a discussion on a topic for 12 hours Researcher asks specific questions and guides the discussion Nonrepresentative samples Emphasis on discovering unanticipated findings and exploring hidden meanings May need to conduct until a saturation point is reached Mixed Methods Using both quantitative and qualitative methods to explore the same research question Qualitative Data Analysis Focus on quottextquot Tends to be inductive Focus on interrelated aspects of the setting group or person under investigation Conducted as data is being collected Steps for data analysis 1Documentation 2Conceptualizing Coding and Categorizing Identify and refine important concepts Check for coding reliability


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