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Summary MCRS part 2- Y

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This summary gives a clear overview of the lectures and book together, provided by an honours student.

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  • 10 december 2023
  • 17
  • 2023/2024
  • Samenvatting
  • part 2
  • mcrs
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Summary MCRS second exam
There are 2 types of validity: measurement and research: research validity 
External validity (outside research):
o Population validity  sample needs to be best representant as possible
o Ecological validity  where you experiment takes place, in which circumstances
Internal validity (inside research): causality  co variance, time order, non-spuriousness

High control = high interval validity (certain about conclusions) experiments  low external validity
Low control = low interval validity (uncertain about conclusions)  high external validity: results are
applicable beyond the experimental setting
Attempts to increase internal validity can lower external validity (and vice versa)

SAMPLING
A sample is a selected segment of a population presumed to represent that population
o Probability sampling: random selection  very unit has equal chance of being selected, the
researcher has no control
o Non-probability sampling: based on judgment of the researcher  does not permit
generalization to a wider population

Sample size depends on:
o Purpose of the research
o Desired level of statistical confidence
o Homogeneity of the population
o In practice, the time and resources aviable for research

Probability sampling:
 Random sampling: e.g. throwing dice, drawing names out of a hat, lotteries
 Multistage cluster sampling: population is divided into clusters, then a random selection is
selected and all the participants in the chosen clusters are selected
 Stratified random sampling: to ensure that all the groups of interest are represented in a
sample, the population is divided into separate groups (strata) and then the random selection
 Systematic Sampling: means sampling every nth person on a list- for example, taking every 10th
or every 100th person listed in a phone book  the interval you select is the sampling interval

Non-probability sampling:
o Convenience sampling  elements are selected that are the most easy
o Snowball sampling  form of convenience sampling that occurs when you rely on members of a
network to introduce you to other members of the network
o Purposive sampling  based on the idea that a specific person or media content will meet
specific criteria the researcher may have
o Quota sampling  based on attempts to replicate in a sample the features that the researcher
thinks are important in the population
o Volunteer sampling  form of sampling that researcher directly recruits volunteers

Sample: the bigger the better (until a certain point)
However, a bigger sample never makes up for a bad sampling produce

Partial non-response: respondent stops halfway
Unit non-response: selected respondent does not participate in your study
 Unreachable/ speaks different language/ he or she does not want to participate

,Consequences:
- You need a larger sample
- External population validity lower, you may not have reached specific subgroups

Wat to do:
- Start over (most of the time not possible)
- Be transparent about sample and non-response and reflect on generalizability of results
(especially in case of non-probability)
- Check representativeness of your sample

SURVEYS: PUTTING NUMBERS ON OPINIONS
Survey: captures public opinion at a point in time (several surveys in a row can capture opinion over
time) and use formatted standardized rather than open-ended questions

Advantages: Disadvantages:
 Relatively low cost o Provides information more than understanding
 Relatively fast delivery o Increasing public resistance
 Rapid data processing o Difficult to explore issues in depth
 Can research large populations o No control over response rate
o Generally limited to scaled or check-list questions
Types of survey:
- Cross-sectional  at one point in time capturing the publics opinion
Disadvantage: could produce remarkably different results on another time
Least expensive but cannot determine cause and effect
- Longitudinal  over time, with several surveys
More expensive, but provide a better sense of cause and
effect, different types:

Trend study
 Measures the same items over time using the same questions but drawing different samples
from the population each time
 Not clear why change occurred because one is not collecting information from the same
individuals over time
 Examines trends in public opinion
Example: comparing public opinion regarding gun control in 2010, 2015, 2020

Cohort study
 Collects data from different individuals within the same cohort
 Provides more detail than a trend study, but determining cause and effect is still a problem
because the same persons are not studied over time
 Examines changes in a cohort across time
Example: students communication science international track who started their studies in
September 2021

Panel study
 The same individuals are retained to answer questions over time
 Examines changes in individuals across time
 Surveys do not necessarily include same questions
 Panels can also be used for cross-sectional surveys (one point in time)
Example of a panel: 5000 respondents who were randomly selected form the general Dutch
population. They receive surveys: survey at wave 1, survey at wave 2, survey at wave 3

, Cross-lagged panel survey
 The best form of survey for “determining” cause and effect (still only indication)
 You measure independent and dependent variable at several time points (hence surveys need
the same questions at each wave)
 You need panel data

Prevent social desirability bias
o Indirect questions (third party reference)
o Show that it is ok to answer in a way that is not socially desirable

Item non-response
o Respondent does not understand a question
o Respondent does not want to answer a question (to intimate, threatening)
Consequence: external validity lower  when item non-response is associated with characteristics of
the respondent (e.g., with demographics)
What to do?  change questions/ pre-test questions/ change answer format

How to pre-test:
 Ask respondents to fill in questionnaire and add evaluation question (ask for feedback)
 Cognitive interviewing: use think-aloud method and ask respondents what they think when
filling in the questionnaire


EXPERIMENTAL DESIGNS
Surveys are a correlational design (not sure of causality)
You need to use experiments when you have a causal hypothesis

Randomization: eliminates all systematic differences between participants in different conditions
Control group: independent variable is absent
Based on level of control: pre-experiment  quasi-experiment  true experiment

Types of experimental designs
One-group pretest-posttest design O1 X O2
 Type of a pre-experiment
 Measure same people once before and once after manipulation
 Low internal validity (cannot rule alternative explanations)

Two-group pretest-posttest design X O2
 Quasi-experiment (because no random assignment) O2
 Two different groups
 Measure before and after manipulation
 Problems: what if groups were different anyway?

Quasi-experiment: Two-group pretest-posttest design O1 X O2
o Independent variable cannot be randomized (e.g. personality characteristic) O1 O2
o No random assignment at individual level, but at group level
o Inclusion of control group

True experiments maximize internal validity  essential ingredients:
Manipulation: ensures that cause precedes the effects
Comparison: ensures effect does not occur naturally
Random assignment: ensures there are no other explanations for the effect (replication required)

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