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Task 4: Norms and Test Standadisation (Van Breukelen (Multiple regression:…

- - - - Raw scores: most basic level of information from a test, initial outcome of testing, alone totally meaningless  need some reference point to compare the results
        
        RAW SCORE TRANSFORMATIONS
        
        Percentiles
        
        Normalising standard scores: conversion of percentiles into normalised standard scores
        
        Use percentile for each raw score to determine the corresponding standard score  do this for every case in a nonnormal distribution  normally distributed standard scores
        
        standard scores (z-scores)
        
        Retaining relative magnitudes of distances between successive values found in original raw scores = use does not distort the underlying measurement scale (advantage over percentiles)
        
        Standardised scores: conceptually identical to standard scores, BUT always expressed as positive whole numbers
        
        T-score: mean of 50 and SD of 10, common scale for personality tests
        
        Transformation: or simply: T = 10z + 50
      - Frequency distributions: specifying a small number of usually equal-sized class intervals and then tallying how many scores fall within each interval
        
        HIstogram
        
        Polygon
      - measures of central tendncy
        
        median
        
        mode
        
        mean
      - measures of dispersion/variablity
        
        Standard devoatopm
        
        Variance
      - Normal Distribution
        
        positive skew - when most scores are on the low end (left end) of the scale
    - - Stratified random sampling - stratifying/classifying the target population on important background variables (age, gender, race, social class, educational level etc.) and then select an appropriate percentage of persons at random from each stratum
      - Age norms: as we grow older, we change in measureable ways  depicts level of the test performance for each separate age group in the normative sample
      - Random sampling - all subjects have equal chance of being selected
      - Expectancy tables: portrays the established relationship between test scores and expected outcome on a relevant task
      - Grade norms - depicits level of performance per grade in school (used in schooling)
      - Local norms - representative oflocal examinees - as opoised to national sample
      - Subgrouo norms - consist of the scores obtained from an individual subgroup, as opposed to diversified national sample
- - - - Allows clinician to distinguish which background variables are/ are not predictive of scale scores and therefore relevant to a valid norming procedure
        o Example: here gender was irrelevant, but educational level was relevant for the PCL scales
      - Norms are more continuous and more reliable than those obtained by tabulating the mean and SD of the scale score for different age x gender groups
      - Only advantage of traditional method is ease of use, in all other respects its doomed to fail