Competence II: Ch 12-16 & 22 Flashcards
How important it the independent variable in research studies?
VERY without you do not have a study without something to manipulate (in experiment manipulate the intervention also comparing treatment versus control manipulating group 1 versus group 2)
What does “operationalizing the independent variable” mean?
Operationalizing clearly explicating content of variable determining if it represents variable of interest, limiting differences between treatment and control conditions, and establishing salience of the differences
Provide examples of independent variables as categorical versus those that are quantitative
Categorical independent variable: (groups being compared together), survey, correlation / Quantitative Independent Variables: quasi experimental, experimental and regression (difference here with IV is a measure it’s a scale and continuous numbers on it both IV and DV are continuous and have numbers; numbers being compared to numbers)
What are status variables, and how do they fit into research designs appropriately?
Status variables are not amenable to manipulation because ethical constraints or logical impossibilities; cab assess associations or interaction
How important are dependent variables in research designs?
Provide a way of measuring the effect of having manipulated an independent variable
What are some examples of procedural considerations that should be of concern to those who design research studies? Why is it important to be concerned about them?
Procedural considerations need to be addressed in order to assure that the study is being conducted appropriately (e.g. time involved with the assessments, readability of the materials, order of administration of the instruments and sufficient detail provided in method section of reports
What is the difference between obtrusive and unobtrusive measures, and why is this an important issue in designing research studies?
a. Unobtrusive measures allow data collection without participant awareness and eliminate reactivity; sometimes unethical and difficult to obtain (e.g., natural or contrived settings and archives)
b. Obtrusive measures cover virtually everything else; the challenge is to be as unobtrusively obtrusive as possible in order to minimize reactivity from participants
How do researchers “take great care in identifying the characteristics of study participants” in the absence of random sampling?
ask the participants using a demographic questionnaire
How important is it to get the right number of participants in a research study?
Concerned about being able to publish if don’t get a large enough sample (minimum 50% return rate)
What are the central concepts to all multicultural research?
race, ethnicity, culture
What is the relationship between error variance in research studies and experimenter and participant bias?
- Experimenter and participant bias is related to biological and interpersonal characteristics
- Variety of different sources of bias that can get into the way will hinder finding out what you are trying to find out and confuse you.. need to anticipate and prevent these sources of bias
- Error Variance is variance in results that can be charged to errors that are caused by things that we are trying to control
- Experimenter & participants are people and have biological and interpersonal characteristics that need to be identified and controlled
What steps can be undertaken to reduce the effects of possible experimenter bias?
Experimenter bias can be reduced by avoiding having a single experimenter, analyzing data differences across experiments, specifying characteristics of therapists/trainers used in treatment interventions, and examining the generalizability of data in terms of experimenter/trainer attributes
What steps can be undertaken to lessen effects of investigator and experimenter expectancies?
• Experimenter/investigator expectancies can be lessened by keeping them blind or partially blind to the hypotheses and using strategies to reduce half-hearted efforts
What strategies can be used to reduce bias due to experimental procedures?
a. Strategies for reducing bias due to experimental procedures include making the procedures explicit through careful descriptions, standardizing the procedures, reiterating the procedures with all personnel, training the experimenters, maintaining close contact with all personnel during the study, and checking experimenter performance and for fatigue
What strategies can be used to reduce participant bias?
Strategies for reducing participant bias include keeping the blind or naive to the hypotheses, reducing threat associated with the study, increasing participant honesty, reducing fears about confidentiality, appealing for increased motivation, conducting post-experimental inquiries, using disguise or acceptable deception, performing spot-checks on participant performance, evaluating the reading level of all instruments, and being attentive to participant ability to report their cognitive and affective processes
statistically significant results:
indicates that the results for reach of the conditions are sufficiently different and consequently the null hypothesis of no differences is rejected.
manipulation checks:
goal is to show: 1. Conditions vary on the intended dimensions, 2. That conditions do not vary on other dimensions 3. Treatments are implemented in the intended fashion; no assurance that experimental manipulation will achieve its purpose so manipulation checks look into the following three conditions
non-significant results:
can be due to multiple factors beyond lack of true effect including: inadequate statistical power, insensitive instruments, violated assumptions of statistical tests, careless procedures, and bias. Or poorly designed IVs
target population
well defined set of people that the study hopes to generalize to
sampling theory:
involves selecting samples that reflect larger or total populations. Technically the population is the observations or scores of people rather than the people themselves.
participant pool:
group of people who both fit the definition of target population and are accessible
good enough principle:
non-random samples can have characteristics such that generalization to a certain population is reasonable. - documenting important characteristics of the sample (e.g., age, gender, race, etc.); rule of thumb = more is better; NIH studies = information about women and members of minority groups must be included
statistical power analysis:
power is the probability of rejecting the null hypothesis when the alternative is true, or likelihood of detecting an effect when the effect is truly present. Dependent upon (1) particular statistical test used (2) the alpha level (3) the directionality of statistical test (4) the size of the effect (5) the number of participants. POWER MUST BE CALCULATED FOR EACH SPECIFIC STATISTICAL TEST
specifying the effect size prior to a study
this is problematic because if you knew the effect size before the study was conducted there would be no need to conduct the study. Effect size must be stipulated before the number of participants can be determined.
Race
presumed classification of all human groups on the basis of visible physical traits or phenotype and behavioral differences (ex. Skin color, physical features, language). Include biological component
Ethnicity:
ones national origin, religious affiliation, or other type of socially or geographically defined group, nationality, culture, language. Broad interpretation: ethnicity shares culture and physical features; narrow interpretation: ethnicity restricted to cultural differences
Culture
differences in psychologically, anthropologically, sociologically. Objective culture (human made part of environment buildings, roads, homes, tools) Subjective culture(values, believes, attitudes, role definitions)
