PY1501.8 ~ {Questionnaire design: Items and Scales}
to measure a psychological trait or attribute items can be generated from
psychological theory + systematic search
generating items from theory
start with wekk defines theory about a psych trait
create questions on the basis of the theory
also generate reversed questions
generating items by systematic search
semantic links [ look through: dictionairies + web pages related to construc being measured]
consult experts [ focus groups + key informants + clinical observation]
content validity
ensure items cover the full range of domain [ask questions to cover each area]
ensure questions only ask one thing
readability [ensure questions can be understood by someone with reading age of 8 years] + culutural appropriateness + language issues/translation
scaling
the process of transforming variables so that they have specific statistical properties, such as a common range or standardization. it ensures that all variables contribute equally to the analysis, particularly when they are measured on different scales or units.
what are the 2 approaches to scaling
comparative scaling + direct estimation
comparative scaling
group of techniques used to measure people's preferences / perceptions between items
types of comparative scaling
the paired comparison technique
thurstone’s method of equal-appearing intervals
steven’s scaling
guttman Scaling
paired comparison technique
method is psychometrics + survey research that involves comparing 2 items at a time to assess preferences + attoitudes or other relative characteristics
how does the paired comparison technique work
forces participants to make decsions between pairs rather than assessing them each independently
theory behind PCT
comparative judgement theory + psychophysics [aim to measure relative strength of preferences, perceptions or attributes. main underlying idea is that humans tend to assess things in relation to others rather than in absolute terms
the assump[tions + how paired comparisons lead to an interval scale
each item is being rated according to some latent unobserved psychological dimension, people have an intrinsic perception of the importance for each item which exist on a continuous scale. the underlying true weighting varies around a mean value in a ND
the PCT algorithm
select a small number of items that measure the phenomenon of interest + get a number of judges to compare all possible pairs of items and rate which of each pair most strongly indicates the phenomenon of interest + convert the proportion of raters preferring one over the other to a z-score + average the z-scores for each item individually+ mean z-score provides an interval scale for the phenomenon of interest
scaling by direct estimation
techniques where participants are asked to provide a direct quantitative estimate of the attribute of interest often through self-report measures or scales. goal is to obtain a clear, direct + numerical value for psych/emotional state being measured
response formats for direct estimation
dichotomus response
rating scale with anchor points
visual analogue scale
asking the questions DE
ask questions covering freq vs intensity vs duration [how often/ how bad is it/ fow how long]
time period of interest [how are you feeling now, today etc]
response formats DE
too many steps become meaningless + leads to poor reliability & loss of info
more than 7 categories is ideal
labelled boxes get endorsed more
DE vs CS
de - widely used + quick to develop + easily understood by users and consumers + vulnerable to some biases + not guaranteed to produce interval level scaling
cs - guarantees interval level scaling + takes longer to develop
benefits of using scales
to improve accuracy and reliability of measurement
to obtain interval level measurement
improving reliability + validity
classical test theory [ observed score = true score + error]
errors are random [ND + independent]
reliability = true score/observed score
what has the same advantage that repeated measurements have
items that measure the same latent variable - if you take the avg of all measurements, those that are too high will cancel out those that are too low [mean measurement provides more accurate estimate of the true value than any individual measurement]
why can't we just repeat the same question again and agin
only works for certain attributes where measurements are independent whereass for psych attributes the single items never fully characterise the latent variables cause measurement are not independent [people have memories, rulers don't]
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