The Measurement Process

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- What is the point of research if it can't be measured
- Measurement is the assignment of values to outcomes
- How do we measure height?

Principles of measurement in Research - 3 ideas

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- an outcome variable belongs to one of four levels of measurement (Nominal, Ordinal, Interval, and Ratio)
- The qualities of one level, are also characteristic of the next level
- e.g., ratio measures such as height also capture ordinal information

- The higher the level, the more precise the measurement process, and closer you will be to the true outcome of interest.

- e.g., ratio measures such as height also capture ordinal information

Levels of Measurement

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- The relationship between what is being measured and the numbers that represent what is being measured
- Every variable must be operationally defined:

Variables are Categorical or Continuous

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- Categorical
- Names are distinct entities
- Simplest form is binary variable; can only go in one of two categories. eg male v female
- Continuous Variable

- Can take on any value on the measurement scale. eg: time on a stopwatch

- Names are distinct entities
- Simplest form is binary variable; can only go in one of two categories. eg male v female
- Continuous Variable

Levels of measurment in order of complexity

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- Nominal
- Ordinal
- Interval
- Ratio

Nominal Variable

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- Nomin = name
- Differ in quality rather than quantity
- Characterises observations in a manner where they can only be placed in one category eg: eye colour
- May be given names or numbers but these have no intrinsic value. such as with NRL Jerseys
- Most IV's are nominal

Ordinal Variable

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- Like nominal they permit classification tell us the order in which things have occurred
- Ordinal scales have no absolute zero point. ie: Horse racing
- Imply nothing about how much greater one ranking is than another

Interval Variable

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- Equal intervals on the scale represent equal differences in the value measured
- eg: temperature, although equal, be sure to consider interpretation of values along the scale.

- eg: temperature, although equal, be sure to consider interpretation of values along the scale.

Ratio Variables

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- Ratio meaning calculation
- Build on interval but also requires the ratios of values are meaningful
- Requires a true zero point not an arbitrary one

Continuous variables are continuous or discrete

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- Continuous = any level of precision such as time
- Discrete = certain defined values such as number of children in a family

Categorical - Distinct Category

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- Nominal Variable - more than two
- Ordinal variable - Same as nominal but a logical order ie: fail, pass, credit, distinction, high distinction.

Continuous - Distinct Score

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- Interval variable - equal entities represent equal difference
- Ratio variable - Same as interval but scores are meaningful ie: 50kg is twice as heavy as 25kg

Levels of Measurement and complexity

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- Nominal - Categorie
- Ordinal - orders
- Interval - meaningful distance
- Ratio - absolute zero

Principles of measurement in research

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- An outcome variable belongs to either nominal, ordinal, interval and ratio
- Characteristic of the next level eg: ratio measurements such as height also capture ordinal information
- The higher the level the more precise the result and closer you will be to the true outcome of interest

Principles of Measurement in Research - Points to Ponder

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- More information increases the power and utility of your results
- Sometimes you will be limited to what is available to you
- Always define your variables in ways that maximise the use of your information
- In behavioural and social sciences most data is usually nominal or ordinal however test scores yield interval level data
- How you choose to measure an outcome defines the level of measurement
- Variables may not completely fit this rigid framework in the real world

Reliability and Validity

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- You're only as good as your tools
- You can have a great research question but will not succeed if your tools are unreliable
- The consistency and validity of a measurement tool are critical to good research
- Faulty tools lead to errors in accepting or rejecting the null hypothesis

Reliability

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- When measuring we assume that there will be a discrepancy found
- The True value of measurement
- Reliability decreases as error increases
- Reliability =
__True Scories__

__True Scories__True Score + Error

Ways to increase measurement reliability

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- Increase number of items or observations
- Eliminate ambiguity
- Standardise conditions
- Moderate difficulty
- Minimise effects of external events
- Standardise instructions and Standardise scoring

How to measure reliability

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- We use correlation; a measure of relationships between things
- We can calculate a number that provides a gauge of relationship direction and strength
- Called Correlation Coefficient

Correlation Coefficient

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- This is a measure of the direction and extent of the relationship between two sets of scores.
- Range of a correlation coefficient is from -1 to +1

Pearson's r

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- Pearson's product moment correlation coefficient
- This coefficient will provide a gauge of how similar scores on a test are from time 1 to time 2
- This is one form of reliability

Types of Reliability - Test-Retest

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- A Measure of stability; how stable is a test over time,
- Measuring the same individuals at two points in time

Operational Definition

The operational definition of a variable is the ** specific** way in which it is measured in that study

Name the different types of Reliability (4)

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- Test-Retest
- Parallel Forms
- Interrater
- Internal Consistency

Types of Reliability - Parallel Forms

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- Different forms of the same test given to the same group of participants
- You might see this in a practice effects test

Types of Reliability - Interrater

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- Evidence of reliability when multiple raters agree in their observations of the same thing
- Rater to Rater, rather than time to time

eg: observational research

Types of Reliability - Internal Consistency

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- Uses responses at only one time
- Focusses on consistency of items

Types of Reliability

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- Test-Retest
- Parallel Forms
- Interrater
- Internal Consistency

Measuring what we intend to . . .

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- Our measues should be reliable and valid
- Validity refers to the results of the test
- It is never all or nothing
- Validity of the results interpreted in teh context where the test occurs
- Are the results understood within the context of the purpose of research?

Name the Types of Validity