This is a part 2 of the MCRS notes that focus on the later chapters of the modules, they will complete your knowledge for your exam and will help you perfect your SPSS and statistics knowledge skills.
1. INTERNAL-EXTERNAL VALIDITY } RESEARCH VALIDITY
● EXTERNAL VALIDITY : outside of your research
● population validity - do not exclude any groups within
your population / if you exclude then at least be
transparent
● ecological (environment) validity
● INTERNAL VALIDITY : concerns something within your research
- measurement validity
● the relationship we find should not be spurious
● concerns the validity of your conclusions ,
● concerns the certainty with which you can cause casual relationships
with your research
2. SAMPLING - PROBABILITY SAMPLING
● You need a sample that is a micro version of the entire
population
- simple random sample = each subject has the same chance of being
selected
possible bias :
- undercoverage (not everyone is included)
- sampling bias (not everyone is equally likely to be included)
- non-response bias
- response bias
TERMS :
● element/unit = single entity in a population , together all elements
form the population
, ● stratum = subject of elements form the population that share a
characteristic
● census = a numeration or count of all elements in a population
● sampling frame = a list of all the elements in a population that can be
individually identified ;
- can overlap with a census
- provides a way of contacting elements
SAMPLING ALTERNATIVES :(almost as good)
1. Random multistage cluster sample: if you don't have a good
sampling frame
you identify a large number of clusters -> random selection ->
selection from the random selection } sample
2. Stratified random sample:
you divide population in separate groups (strata)-> random selection
} sample
4. NON-PROBABILITY SAMPLE
● Same elements in the sampling frame either have no probability to
be selected or their probability is unknown .
- 4 CATEGORIES
● Convenience sampling (convenient elements-easily
accessible)- risk of bias is hightH
● Snowball sampling (samples contact new samples -
useful for closed community)- when the participants
refer new participants - risk of bias is high
● Purposive sampling (chosen sample based on the
judgment of the researcher) -risk of bias is high
● Quota sampling (distinguished according to
characteristics) - risk of bias is high
5. CORRELATIONAL DESIGNS(we just measure)\ no manipulation sos
-> Cross-sectional design = a cross-section population is considered at one
specific point- measured once
-> Time-series design = can refer to one person being measured at several
points in time
,-> Panel (time-series cross sectional) design
- same group of people
● longitudinal = any study that follows one or more participants over a
long period of time
● time-series = correlation : 1 person measured over time or groups
● repeated measures = experimental (persons measured over time in
all conditions)
CORRELATIONAL DESIGNS
ADDITIONAL MICRO LECTURE -FAM
- Prevent social desirability bias (validity threat)
● Indirect questioning
● Show it is ok to answer in a way that is not socially desirable
READINGS FOR MONDAY
- SURVEY :
● is a series of formatted questions posed to a sample of people
with the expectation that their responses will be returned
immediately or within a few days .
SUMMARY
● Most survey designs cannot assess causal relationships between
variables .
MONDAY’S LECTURE
SURVEYS :
● Capture public opinion at a point in time
● Use formatted rather than open-ended questions
, TYPES OF SURVEYS :
● Cross sectional -> 1 point in time
● Longitudinal -> predictions/changes over time
- trend : different people over time
- cohort : same type of people over time
- panel : same individuals over time
- cross-lagged panel : measures a dependent variable and an
independent variable at two points in time
CROSS-SECTIONAL OR LONGITUDINAL
● A cross-sectional study is the least expensive , but cannot determine
cause and effect
● Longitudinal studies are more expensive , but provide a better sense
of cause and effect
● To determine causality , you need a true experiment . However ,
panel studies with cross-lagged surveys may provide you with some
INDICATION of causality
- population = every person in the group you are studying
- sample = part of population selected for study
- census = study of entire population
- parameters = describe a population
- statistics = describe a sample
TUTORIAL FOR MONDAY
● What type of validity is generally speaking lower in survey design ?
- internal validity
● When is non-response a problem?
- cause the sample is not representative of the population
- Question for survey : shouldn't have effect but should have the
word CORRELATE , RELATE , IN RELATION, WHAT IS THE RELATION
BETWEEN THIS AND THIS , ASSOCIATION
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