Midterm Flashcards
Measurement Validity
When the measure measures what we think it measures.
Generalizability
The extent to which info gleaned can be used to inform about population as whole (External validity)
Causal validity
Internal Validity - when hypothesis that A causes B is correct.
3 Stages of forming a good research question
- identifying 2. refining 3. feasible?
Theory
logical interraled set of proportions about empirical reality
Inductive Reasoning
observed data –> generalization which explains relationships between objects observed
(QUALITATIVE)
Deductive Reasoning
theory –> hypothesis –> define variables and operations –> implement measurements and observations to see if they confirm/fail hypothesis
(QUANTITATIVE)
Dependent Variable
variable that DEPENDS on another variable
Positive Association/Correlation
going in the same direction
Negative Association/Correlation
going in different directions
Theoretical Statement
social networks positively influence psychological wellbeing.
Moderating Variable
Variable that influences relationship between variables
Mediating Variable
Variable that explains the relationship between variables
Problem Formulation
- Problem area (something you are interested in). 2. Idea (what are concepts and possible variations)
- Theory (how are concepts related to each other)
Operationalization
How we measure variables included in a study
Direct Measurements
Visual, physical symptoms, interviews, self-administered questionnaire, written records
Indirect Measurements
Unobtrusive/Indirect observations, content analysis
Nominal Measurement
categories: types of vanilla, milk, etc. (when you can’t order other things) (gender, ethnicity, religion)
Ordinal Measurement
No measureable distance between values, Taste Test: rating of 1-5 (social class, racism, sexism)
Interval/Ratio
measureable distance between values, based on absolute zero, degrees, etc. (meaningful intervals)
Discrete variable
cannot take on all values within the limits (ex: 1, 2, 3)
Continuous variable
variable can take on any variable (ex: 1, 1.25, 1.45, 2)
Measurement Error
- Systematic (social desirability, acquiescence bias, leading questions)
- Random (why respondents feel that way that day, regression to the mean, multiple rating behr’s, inadequate training)
Reliability
The measurement is consistent
Validity
The results are accurate
Test/Re-Test Reliability
same result after multiple trials
Inter-rater reliability vs. Intra-rater reliability
correlation between 2 raters (inter) single observer of 2 pts in time (intra)
Sampling
Random (probability) and Non-random (non-probability)
Population
The entire set of individuals or other entities to which study findings are generalized
Sample
Subset of population used to study whole
Sampling Frame
Structure for choosing sample (ex: list of Loyola students)
Sampling Units
units listed at each stage of multi-stage sampling design
Units of analysis
from whom or what are you collecting data (ex: individuals, households, orgs)
Ecological Fallacy
making a generalization based on a small sample
Representative Sample
looks like population from which it was selected
Unrepresentative Sample
doesn’t look like the population from which it was selected
Census
a study of the entire population (assumes perfect response)
Sample population generalizability
if sample is generalizable to the target population
Cross-population generalizability
If sample cannot be generalized to target population
Sampling Error
Any diff between characteristics of a sample and characteristics of population from which it was drawn
Recruitment Strategies for Diverse Populations
- involve key members of community/orgs
- demonstrate benefits to community
- understand cultural barriers
- train interviewers
- go where potential participants are
Simple Random Sampling
identifies cases on basis of chance