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99 Cards in this Set
- Front
- Back
an idea constructed by the researcher to explain observed events (a rational idea that is used to explain a phenomenon); an operational definition (explanatory idea about internal states that generate behavior)
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construct
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How well the study’s results support the theory or
constructs behind the research; Whether the theory supported by the findings provides the best available explanation of the results |
construct validity
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How do we maximize construct validity?
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The researcher should use clearly stated
definitions and carefully build hypotheses on solid, well‐validated constructs which have received support from numerous other studies; have a clear definition of the constructs of interest; verify that there is a good match between constructs and operations used to represent them |
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Defined as the degree of confidence that the
inferences about study outcomes based on statistical tests are correct |
statitical conclusion validity
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What are the factors affecting validity types?
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-measurements must be reliable and valid
-useful measures are sensitive -useful tests are specific -should avoid ceiling and floor effects -researcher bias - |
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refers an effect whereby data
cannot take on a value higher than some "ceiling." |
celing effect
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refers an effect whereby data
cannot take on a value higher than some "floor." |
floor effect
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How can researcher bias be lessened?
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-using designs where the researcher is blind to conditions
-comparisons cross-checked for consistency in recordings |
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An ________ _________ is a measure of the
“influence” of a journal • Measures the ___________ with which the "average article" in a journal has been cited in a given period of time • Journal Impact Factors are produced by .....? • Impact factor available thru (1) _______________ ____________ (2) on a journal’s _________ _________ |
impact factors
frequency Thomson Institute for Scientific Information University Libraries; journal's website |
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Journals which publish on more specialized
topics will have _______ impact factors than those which publish on more general topics |
lower
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Other factors influencing impact factors?
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Date of publication
– Size of journal – Average number of citations – Number of review articles – Type of field |
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We’ve now learned about ________ of evidence
and ___________ of evidence in terms of: – Study design (experiment, quasi‐experiment, etc.) – Validity (internal, external, construct, etc.) • The highest quality, strongest and/or most innovative articles will often be the most highly influential – Journal impact factors! |
quality; strength
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What section of a research paper summarizes data and statistical analysis? It uses _____________ statistics and includes tables and figures.
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results section
descriptive |
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_____________ statistics summarize, simplify,
and describe measurements – Measures of “_______ __________: mean, median, mode – Measures of ___________: range, variance, standard deviation |
descriptive
central tendency variability |
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____________ statistics help researchers
interpret the data What are some examples? |
inferential
T‐tests, ANOVA, ANCOVA, Wilcoxon sign‐rank test, Tukey’s HSD, etc. |
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The appropriateness of the descriptive and
inferential statistics for data affect _____ _________ __________ |
statistical conclusion validity
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What are the different scales of measurement?
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Nominal Scale
• Ordinal Scale • Interval Scale • Ratio Scale |
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Naming scale
– Each number reflects a category What are some examples? We can only look at _____________, can't ____ or __________ |
nominal
men/women, type of hearing loss (conductive, sensorineural, mixed); desire to upgrade to AuD (yes/no); code as 1, 2, 3, etc.; phoneme production (correct/incorrect); diagnostic category (stutterer/nonstutterer) frequencies; add/subtract |
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Scale indicating rank order
– Reflects the order, but not the amount What are some examples? We can calculate the _________ rankin but not much more. |
ordinal
ranked severity groups, socioeconomic status (low‐, middle‐, upper class), rank in class, stimulus complexity (easy, moderate, difficult) mean |
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can only be represented
by integers (whole numbers like 1, 2, 3…) – Nominal and ordinal data theoretically capable of taking on fractional units of measurement – decimals (sometimes rounded) – Interval and ratio data |
discrete variables
continuous variables |
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Scale with equal intervals
–The scale indicates amount, but with no zero point What are some examples? We can .... |
interval scales
temperature on the Celsius scale, most assessments (TOLD, PPVT‐R, CELF) Can add subtract, but typically not multiply or divide |
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Scale that fits the number system well
– Includes equal intervals and a true zero ‐ “zero means zero” ; "score" data Examples...? We can... |
ratio scale
7 Ratio Scales • Scale that fits the number system well – Includes equal intervals and a true zero ‐ “zero means zero” • Examples: time, distance, frequency, weight, volume, etc., vowel duration, sound frequency, air pressure, number of misarticulations, diadochokinetic rate, speech intelligibility score Perform any mathematical equation |
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__________: Experiments, comparative studies
____________: Correlational studies, survey research, retrospective research _______: Observational research, case studies, Interview research* ________: Interview research*, narrative research, testimonials *Strength is higher if structured interviews are used |
strong
medium low lowest |
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2‐D graphs have:
– An_________ (abscissa) – A ________ (ordinate) |
x-axis
y-axis |
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Frequency or grouped frequency can be
represented as either: ___________ Bar graph showing a count on the y‐axis – _______ __________: Line graph showing a count on the yaxis |
histogram
frequency polygon |
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shows the %
or proportion of scores that fall within each range of values – Similar to histogram, but y‐axis is different |
relative frequency distribution
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whole pie is 100%; pieces of pie
represent fractions of 100% for each category |
pie chart
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Some distributions are ______________ (right side is the
mirror image of the left side) – E.g., ________ distributions: “bell curve” • Other distributions are not symmetric – ___________ _________: “Tail” tends toward positive direction – ___________ ____________: “Tail” tends toward negative direction |
symmetric
normal positively skewed negatively skewed |
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We may want to know where “most of the
participants fall” on the distribution – This is called the _________ ___________ of the distribution – Measures of central tendency include __________ , ____________, ___________ |
central tendency
mean median mode |
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Central tendency = _______ of a distribution
• Measures of central tendency: – _______ (average) – ___________ (middle score in rank‐ordered list) – _______ (most frequent score) |
mean
median mode |
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___________ – one most frequency score
__________ – two most frequency scores |
unimodal
bimodal |
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We can quantify __________(or horizontal spread)
of a distribution by using.... (2) ____________ = (standard deviation)2 (square of standard deviation) ___________ _____________ = (variance) (square root of the variance) |
variability
variance & standard deviation variance standard deviation |
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A common type of unimodal distribution is the
____________ distribution |
normal
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To calculate the variance, follow these steps:
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– Work out the mean (average of the numbers)
– Then for each number: subtract the mean and square the result (the squared difference) – Then work out the average of those squared differences This gives you the variance! – Standard deviation is the square root of the variance |
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In a histogram, counts go on the ____ axis.
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y-axis
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__________ statistics summarize, simplify,
and describe measurements. They include measures of ____________ __________ (mean, median, and mode; and measures of _______________: range, variance, SD. |
descriptive statistics
central tendency variability |
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____________ statistics help researchers
interpret the data. These include: T‐tests, ANOVA, ANCOVA, Wilcoxon sign‐rank test, Tukey’s HSD, etc. |
inferential statistics
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_________ _________ take into account (a) group mean differences relative to (b) ____________ and (c)
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test statistics
variability number of participants |
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_____________ ______________ statistics provides a standard way of telling whether differences in means across levels of the IV(s) outweigh variability in each level relative to number of participants
• If the inferential test statistic passes a specified __________, then there is a significant effect of that variable; otherwise there is not a significant effect. |
inferential statistics
threshold |
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If there is statistical __________, then there’s no
significant effect of the IV(s) If there is statistical __________, then there is a statistically significant effect of the IV(s) |
equality
difference |
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What are examples of some test statistics?
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t scores (t-tests), z scores (z-tests), F (for ANOVA)
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“Cutoff value” specifies the boundary between an extreme score from a non‐extreme score.
If a test statistic is in the “_________ __________ region”, then we conclude the IV had a statistically significant effect |
extreme score region
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What are the locations of the critical region boundaries for three different levels of significance? .
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α = .05,
α = .01, and α = .001 |
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Descriptive statistics for a sample are referred to as _________ ___________.
– Mean (M), standard dev (s), variance (s2) |
sample statistics
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_________ ___________are abstract or “ideal” values of sample statistics
– Mean (μ), standard dev (σ), variance (σ2) |
population parameters
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What is the first step in the logic of inferential stats tests? What are the 2 possibilities? These are stated in terms of ___________ _______________ like μ, σ.
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Identify & state each hypothesis.
The levels of the IV are equal The levels of the IV are not equal population parameters |
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What is step 2 in the logic of inferential stats tests?
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Set the criteria for a decision:
2 substeps: - determine the statistical test - determine the cutoff value for the distribution that separates normal from extreme scores |
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___________ _______________ refers to how subjects are chosen to be part of a study. It refers to drawing a sample from the population in a manner that ensures that each member of the population has an equal change of being chosen for the sample.
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random sampling
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________________ ____________ is a requirement of a true experiment in which an experimental group and a control group are formed by the experimenter. It is achieved when each subject is just as likely to be assigned to the control group as the experimental group.
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random assignment
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Research that focuses primarily on theory testing is often called _________ research. _____________ research seeks to go from data directly to a real-world application.
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basic
applied |
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What is the college sophomore problem?
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The worry that, because college sophomores are the subjects in an extremely large number of psychological investigations, the generality of the results is in question.
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What is the idea that a new theory in science must make contact with previously established empirical facts? To be considered an advance, it must not only explain new facts, but also account for old ones.
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principle of connectivity
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The principle of __________________________ involves scientists and those who apply scientific knowledge making a judgement about where the preponderance of evidence points. It is a useful tool for the lay consumer of scientific information and particularly useful in evaluating psychological claims. It urges us to base conclusions on data that arise from a number of slightly different experimental sources.
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converging evidence
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A design known as the _____________ has been used to investigate the televised-violence/aggressive behavior issue.
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field experiment
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The ______________________________ refers to the failure of some people to respond with help when observing another individual in an emergency situation.
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unresponsive bystander phenomenom
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To conclude that there is a significant causal relationship between variable A and behavior B does not mean that variable A...
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is the ONLY cause of behavior B
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A factor that influences behavior may have different effects when operating in conjunction with another factor compared to when it is acting alone. This is called the concept of _____________. The magnitude of one variable may depend on the level of another.
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interaction
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____________________ means that it is more likely than not, but does not hold true in all cases.
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probabilistic trend
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The prediction of outcomes based on group characteristics is called ______________________.
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aggregate/actuarial prediciton
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_____________________ is the tendency for people to see links between events in the past and events in the future when the two are really independent.
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gambler's fallacy
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What is important when dealing with multiple causation?
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interactions
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For IV #1... (A,B)
What does H0 say? What is the equation that illustrates this? What does H1 say? What is the equation that illustrates this? |
“The levels of the IV are statistically equal
- There is no difference between the levels” H0: uA = uB "The levels of the IV are statistically nonequal - There is a difference between the groups” H1: uA ≠ uB |
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What is step 3 in the logic of inferential stats tests?
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compute test statistics from the actual data
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What is step 4 in the logic of inferential stats tests?
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make a statistical decision and interpret the results relative to the research question.
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What are the potential benefits of studying more than one IV in a single study?
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-time/effort/cost
-possibility of looking for interactions among different variables |
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An unexpected pattern of data
in which one or more condition(s) do not follow the trends seen for the individual IV’s in the rest of the study |
interaction
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A study that concludes that there are very different outcomes for men and women under different drug dosages revealed the ____________ of IV of gender and IV of drug dosage. Thus, the ________ of drug dosage depends on whether the participant is male or female.
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interaction
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Interactions become clear when studying two IVs simultaneously. This is done using a ____________ study, or one that has more than 1 IV.
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parametric
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________________ is a study where there is more than one IV and there are participants in all possible pairings of levels of the IV’s. These are the norm in studies with more than 1 IV.
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factorial
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First, determine how many ______ there are. This will tell you how many possible ___________________ and _______________ there are. For each, there will be a separate ________________.
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IVs
main effects interactions test statistic |
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A single IV will have...
Two IV’s have... |
one pair of hypotheses for each DV
3 pairs of hypotheses for each DV (one relating to possible main effect of IV 1, one for main effect of IV 2, one for interaction of IV 1 and 2 |
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In an experient w/ one IV ; three levels (multivalent study - experiment or quasiexperiment):
Level A, Level B, Level C – H0: ““The levels of the IV are statistically equal - There is no difference among the groups” H0: uA = uB = uC – H1: “The levels of the IV are statistically nonequal - There is a diff. among the groups” H1: uA ≠ uB and/or uB ≠ uC and/or uA ≠ uC (*post-hoc test needed) |
lala
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1. One IV with two levels (bivalent
study - experiment or quasi-experiment): Level A and Level B – H0: “The levels of the IV are statistically equal - There is no difference between the levels” H0: uA = uB – H1: “The levels of the IV are statistically nonequal - There is a diff. between the groups” H1: uA ≠ uB |
lala
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Interaction between IV #1 and IV #2:
– H0: “IV #1 affects all levels of IV #2 in a statistically equal manner” – H1: “IV #1 affects one or more levels IV #2 in a statistically unequal manner” – No equations required |
lala
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Cutoff values depend on ________________________ given by:
– Number of ____________ AND/OR – Number of ________________ |
degrees of freedom
participants levels of the IV |
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This type of statistical test is based on the assumption that data fit a particular shape or distribution (e.g., ‘Gaussian distribution’). What are some examples?
_____________ tests are not based on this assumption. – Examples: Chi-squared test, Wilcoxon test, Mann-Whitney test, Kruskal-Wallis test |
parametric
t-test, ANOVA (f) nonparametric |
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If you have one IV with two levels, you use a ...
If you have one IV with three or more levels, you use a(n)... If you have two or more IVs, you use... |
t-test (or ANOVA)
ANOVA ANOVA |
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What is the "extreme" region of a distribution?
Example: With df = 20, the critical t value is +/-2.09. If we get t(20) = 5.73, it’s significant! (p < .0001) |
5% or smaller portion of the curve
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What are the (3) types of causation?
_______________: Where a variable is necessary and sufficient to produce an effect on a DV _________________: A causal variable might be necessary for an effect on the DV, but the effect depends on another variable. ______________: A causal variable might be neither necessary nor sufficient, but its presence increases the statistical probability of an effect. |
strongest form
weaker form weak form |
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Any variable that confounds the ability of the chosen sample to represent the population parameter from which it was drawn (bias in representation due to selection, affects external & internal validity __________________________
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selection bias
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How is selection bias minimized?
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-Using random assignment to the levels of IV
-Also by matching participants in terms of groups -Developing well-defined inclusion criteria -Develop exclusion criteria to eliminate unwanted participants that might bias a sample -Sampling as close to randomly as possible |
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Defined as validity of the inference about
whether the causal relationship holds over people, settings, treatment variables, measurement variables, and time ________________________ |
external validity
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What are the (4) types of external validity?
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population validity
treatment variation validity temporal validity ecological validity |
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__________ describes an all‐inclusive data set about which researchers want to draw a conclusion.
A _________ is just a subset of the population. There will inevitably be some amount of ______________, i.e., difference between the measures collected for a sample and the population it’s believed to represent |
population
sample sampling error |
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This refers to the ability to generalize from the sample in a study to a larger population. The _____________ population is the larger population to whom the results are generalized. The ____________________________ population is the one that is available to the researcher.
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population
target population experimentally accessible population |
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How can generalization be achieved easily?
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If the researcher uses random selection
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This involves drawing observations from a population so that each individual has an equal chance of being selected _________________. This is different than __________________, which sets out to create equivalent groups by balancing them based on specific characteristics.
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random sampling
random assignment |
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____________________ is a sampling method where each individual has an equal probability of being selected, "true random selection."
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simple random sampling
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___________________ involves dividing a population into subgroups called strata to assure that certain segments of the population are adequately represented in a sample. ______________ means a subdivision/group.
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stratified sampling
strata |
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________________________ refers to the extent to which results of the experiment can be generalized across time.
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temporal validity
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____________________ refers to the generalizability of results across variations in treatment. It's an issue because the administration of the treatment can vary from one administration to the next.
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treatment variation validity/transferability
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______________________ refers to the degree to which behaviors that are observed in a study reflect the behaviors that occur in natural settings.
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ecological validity
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Refers to the extent that causal inferences are justified based on observed changes in a DV in response to systematic variations in an IV
The strength of depends on to what extent extraneous variables have been removed from the study. |
internal validity
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An most important possible threat to internal
validity is not having a high enough constraint study design How do we minimize this? |
study design threat
random assignment manipulation to remove extraneous variables |
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The fact that an individual changes/matures over time
What is the problem with this? |
Maturation
There is no control group to compare for effects of natural maturation |
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Effects of previous testing on performance
What can we do to guard against this? |
testing effects
use diff questions/assessment wait a long time before reassessing |
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A change in a DV due to a tx effect that is not immediately observable but tends to become increasingly observable over a span of time
To guard against this...? |
sleeper effect
plan appropriate treatment interval and track participants after study has ended |
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This is any event between the beginning of a treatment and the measurement of the DV that could produce the outcome
How can we minimize this? |
history
make sure no new events occur after beginning of tx |
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Refers to the fact that some individuals 'drop out' before completing a study
Ways to minimize? |
attrition
give incentives for participating, enroll new participants in the study |