100% satisfaction guarantee Immediately available after payment Both online and in PDF No strings attached
logo-home
Previously searched by you
Previously searched by you
logo
Summary Measurement Theory and Assessment II - EXAM PREP CA$9.72   Add to cart
Quickly navigate to
Preview
  2.  
  3. Vrije Universiteit Amsterdam (VU)
  4.  
  5. Meten en Diagnostiek 2 (P_BMETDIA_2)

Summary

Summary Measurement Theory and Assessment II - EXAM PREP
 67 views  7 purchases
  • Course
  • Meten en Diagnostiek 2 (P_BMETDIA_2)
  • Institution
  • Vrije Universiteit Amsterdam (VU)

Measurement Theory and Assessment II - EXAM PREP Lecture 1. Introduction Lecture 2. Linear Regression Lecture 3. Logistic Regression  Lecture 4: Test Dimensionality               Lecture 5: Exploratory Factor Analysis (EFA) (Multiple factors) Lecture 6: Confirmatory...

[Show more]

Preview 3 out of 24  pages

Document information

  • November 16, 2023
  • 24
  • 2021/2022
  • Summary

Subjects

  • psychology
  • mta ii
  • measurement theory and assessment ii

Written for

  • Vrije Universiteit Amsterdam (VU)
  • Psychologie
  • Meten en Diagnostiek 2 (P_BMETDIA_2)
All documents for this subject (26)

Seller

avatar-seller
bernarditarichards

Reviews received

Content preview

‭Lecture 1. INTRODUCTION‬
‭●‬ ‭Psychometrics:‬‭assessing the attributes of psychological‬‭tests‬
‭○‬ ‭Interindividual = compare the behavior of different people‬
‭○‬ ‭Intraindividual = compare the behavior of the same person at different points in‬
‭time‬
‭●‬ ‭Criterion-referenced tests‬‭: compare each score with‬‭a‬‭predetermined‬‭cut-off point‬
‭●‬ ‭Norm-referenced tests:‬‭compare each score with a‬‭reference‬‭sample‬‭and‬‭norm‬
‭●‬ ‭Path diagram‬
‭○‬ ‭Latent variable (unobservable)‬
‭○‬ ‭Items (observable)‬
‭○‬ ‭Error (unobservable LV)‬
‭●‬ ‭Psychological theory‬
‭○‬ ‭Decides what is relevant to be measured‬
‭○‬ ‭Informs statistics: make “distributional assumptions” based on theory‬
‭●‬ ‭Statistics: analysis of individual differences‬
‭●‬ ‭Causality‬
‭○‬ ‭Relative items:‬‭item directly and causally related‬‭to the LV‬
‭(correlated)‬
‭○‬ ‭Formative items‬‭: items are not causally dependent‬‭on the‬
‭index variable - items scores determine the test score‬
‭●‬ ‭Properties of Numeral‬
‭○‬ ‭Property of identity‬‭: differentiate between categories‬‭of people (‬‭mutually‬‭exclusive‬‭&‬‭exhaustive‬‭)‬
‭○‬ ‭Property of order:‬‭indicate the‬‭rank‬‭order‬‭of people‬‭relative to each other along a‬‭single‬‭dimension‬
‭(implies transitivity)‬
‭○‬ ‭Property of quantity‬‭: adds information concerning‬‭amount‬‭to the numeral expressed in numerical counts‬
‭of units‬
‭■‬ ‭Absolute zero:‬‭absence of the attribute‬
‭■‬ ‭Relative zero:‬‭assignments of zero to an arbitrary‬‭value‬
‭●‬ ‭Measurement Levels‬
‭○‬ ‭Nominal scale‬‭: Numbers are simply ways to code‬‭categorical‬‭information‬
‭■‬ ‭Property of identity‬
‭○‬ ‭Ordinal scale:‬‭Numbers assigned have meaning in that‬‭they demonstrate a‬‭rank order‬‭of the classes‬
‭■‬ ‭Property of identity & order‬
‭○‬ ‭Interval scale‬‭: Provides a rank order of objects where‬‭differences in scale values express‬‭differences in‬
‭amount‬
‭■‬ ‭Property of identity + order + amount‬
‭■‬ ‭Zero is‬‭relative‬‭(not absolute)‬
‭○‬ ‭Ratio scale‬‭: Property of identity + order + amount‬‭+‬‭absolute zero‬

,‭Lecture 2. LINEAR REGRESSION‬
‭●‬ ‭Linear regression = conditional‬‭MEAN.‬
‭o‬ ‭Conditional mean:‬‭mean score on a variable given the‬‭score on another variable.‬
‭●‬ ‭If we have Y= b0 + b1 * x → no te olvides que es la formula predicted value!! (y=ȳ).‬
‭o‬ ‭b0 : intercept/‬‭constant‬‭: predicted value of‬‭y‬‭when‬‭x‬‭= 0.‬
‭o‬ b
‭ 1 : slope :‬‭regression coefficient‬‭: relationship‬‭between‬‭x‬‭and‬‭y‭:‬ change in‬‭y‭,‬‬
‭as‬‭x‬‭increases by 1.‬
‭o‬ ‭No error.‬
‭o‬ ‭Predicted formula and not observed one.‬
‭o‬ ‭We look at the red line instead of a gray line.‬
‭●‬ ‭Conditional mean‬‭(of y)‬ ‭= Predicted mean‬‭(of y).‬
‭●‬ ‭Notation y I x‬
‭o‬ ‭y given x.‬
‭o‬ ‭Conditional mean‬
‭●‬ ‭Assumptions‬‭distribution of y‬‭linear regression (3):‬
‭1.‬ ‭It needs to be linear regression.‬
‭2.‬ ‭y‬‭is normally distributed for all values of‬‭x‬
‭o‬ F‭ or each value of x, y needs to be normally distributed, and the mean of normal distribution‬
‭equals the predicted score of y‬
‭o‬ ‭Therefore, the‬‭predicted score of y=conditional mean.‬
‭3.‬ ‭Variation‬‭(SD)‬ ‭in scores on‬‭y‬‭is the same for all‬‭values of‬‭x‬‭.‬
‭●‬ ‭No assumptions for‬‭distribution of x.‬
‭●‬ ‭b1‬‭: represent also the difference between the scores‬‭by the two variables. Ex: differences score men and woman.‬
‭●‬ ‭Is the relationship relevant?‬‭→‬‭we need to study‬‭→‬‭R2‬‭=‬‭variance‬‭of y‬‭explained‬‭by x = measure effect‬‭size.‬
‭o‬ ‭var (y) explained variance by x=‬‭b‭1‬ ‭2‬ ‬‭* var (x)‬
‭o‬ ‭var (y) not explained variance by x‬‭=‬‭standard error‬‭of the estimate =‬‭var (e)‬
‭o‬ ‭Total variance (y)‬‭=‬ ‭b‬‭1‬‭2‬‭* var (x)‬‭+‬‭var (e)‬
‭o‬ ‭R2‬‭=‬‭b‬‭1‬‭2‬‭* var (x)‬‭/ (‬‭b‭1‬ ‬‭2‬‭* var (x)‬‭+‬‭var (e)‬‭)‬
‭●‬ ‭Psychological variables → standardize score → multiple ways to do this:‬
‭1.‬ ‭Z-score‬
‭o‬ ‭Z score - does NOT require assumption of normality (M and s)‬
‭o‬ ‭Normalize Z score (based on empirical percentile score) - requires assumption of normality.‬
‭2.‬ ‭Other distributions (t-score)‬
‭3.‬ ‭Percentile score‬
‭o‬ ‭Empirical‬
‭●‬ ‭Does not required normal distribution‬
‭●‬ F‭ rom empirical to‬‭normalize‬‭z score also possible‬‭→ assuming normal distribution from‬
‭population‬
‭●‬ ‭Based on data‬
‭●‬ ‭Theoretical‬‭(table)‬
‭ ‬ F‭ rom z-score to percentile score‬
●
‭●‬ ‭Normally distributed‬
‭●‬ ‭Interpreting scores‬
‭○‬ ‭Variance‬‭: how much the scores in a distribution deviate‬‭from the mean‬
‭○‬ ‭Standard deviation:‬‭square root variance‬

, ‭ ‬ S‭ kewed distribution:‬‭positive → right tail/ negative → left tail‬
○
‭○‬ ‭Kurtosis‬‭: positive → taller / negative → shorter‬
‭○‬ ‭Covariance‬:‭ degree of association between the‬‭variability‬‭in‬‭two‬
‭distributions‬‭(positive/ negative)‬
‭■‬ ‭Provides information about‬‭direction‬
‭○‬ ‭Correlation‬‭: Degree of association between two variables‬
‭(strong/ weak)‬
‭○‬ ‭Correlation coefficient‬‭: number of correlation - from‬‭-1‬
‭to +1‬
‭○‬ ‭Reflects‬‭magnitude‬‭: close to -1 or +1 means that the‬
‭association is very strong‬

The benefits of buying summaries with Stuvia:

Guaranteed quality through customer reviews

Guaranteed quality through customer reviews

Stuvia customers have reviewed more than 700,000 summaries. This how you know that you are buying the best documents.

Quick and easy check-out

Quick and easy check-out

You can quickly pay through credit card or Stuvia-credit for the summaries. There is no membership needed.

Focus on what matters

Focus on what matters

Your fellow students write the study notes themselves, which is why the documents are always reliable and up-to-date. This ensures you quickly get to the core!

Frequently asked questions

What do I get when I buy this document?

You get a PDF, available immediately after your purchase. The purchased document is accessible anytime, anywhere and indefinitely through your profile.

Satisfaction guarantee: how does it work?

Our satisfaction guarantee ensures that you always find a study document that suits you well. You fill out a form, and our customer service team takes care of the rest.

Who am I buying these notes from?

Stuvia is a marketplace, so you are not buying this document from us, but from seller bernarditarichards. Stuvia facilitates payment to the seller.

Will I be stuck with a subscription?

No, you only buy these notes for CA$9.72. You're not tied to anything after your purchase.

Can Stuvia be trusted?

4.6 stars on Google & Trustpilot (+1000 reviews)

71498 documents were sold in the last 30 days

Founded in 2010, the go-to place to buy study notes for 14 years now

Start selling
CA$9.72  7x  sold
  • (0)
  Add to cart