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CAS 301 - Week 4 Notes

by: Caru

CAS 301 - Week 4 Notes CAS 301

Cal State Fullerton

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About this Document

Methods in Behavioral Research - Cosby(12th edition) Chapter 5
Inquiry & Methodology in Child Development
Sarana Roberts
Class Notes
Inquiry, methodology, child development
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This 5 page Class Notes was uploaded by Caru on Wednesday September 14, 2016. The Class Notes belongs to CAS 301 at California State University - Fullerton taught by Sarana Roberts in Fall 2016. Since its upload, it has received 3 views. For similar materials see Inquiry & Methodology in Child Development in Child and Adolescent Studies at California State University - Fullerton.

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Date Created: 09/14/16
CAS 301 ­ Week 4    Chapter 5: Measurement Concepts    ● Reliability of Measures  ○ Reliability​ ​­ the consistency or stability of a measure of behavior  ■ Something reliable would continually yield the same result  ■ Something is unreliable if it yields varied results  ○ True score  ​ ​­ the real score on the variable  ○ Measurement error​ ­ the degree to which a measurement deviates from  the true score value  ■ High measurement error = low validity  ○ In research, you cannot continually test a subject 50 or 100 times;  therefore, it is important to use a reliable measure  ■ This single measure should reflect the person’s true score  ○ Reliability is likely to be achieved when researchers use careful  measurement procedures  ■ Ex. carefully training observers to record behavior  ■ Ex. paying close attention to the way questions are phrased  ■ Ex. recording electrodes are placed on the body to measure  physiological reactions  ■ Reliability can often be increased by making multiple measures  ● Most commonly seen when assessing personality traits and  cognitive abilities  ○ We cannot directly observe the true score and error components of an  actual score on the measure  ■ We can assess the statistical stability of measures using correlation  coefficients(a number that tells us how strongly two variables are  related to each other)  ■ Pearson product­moment correlation coefficient​ ­ most  common correlation coefficient when discussing reliability;  symbolized as ​r  ● Can range from 0.00 to +1.00 and 0.00 to ­1.00  ● A correlation of 0.00 tells us that the two variables are not  related at all  ● The closer a correlation is to 1.00(whether positive or  negative), the stronger the relationship  ● The positive and negative signs provide information about  the relationship  ○ Positive correlation coefficient = positive linear  relationship(/)  ○ Negative correlation coefficient = negative linear  relationship(\)  ● To assess the reliability of a measure, we will need to obtain  at least two scores on the measure from many individuals ­>  if the measure is reliable, the two scores should be very  similar and the Pearson correlation coefficient should be a  high positive correlation  ○ Test­Retest Reliability  ■ Test­retest reliability​ ​­ assessed by measuring the same  individuals at two points in time  ● Ex. the reliability of a test of intelligence could be assessed  by giving the measure to a group of people on one day and  again a week later  ○ We would have two scores for each person, and a  correlation coefficient could be calculated to  determine the relationship between first test score  and the retest score  ● For most measures, the reliability coefficient should be at  least .80 for it to be accepted as reliable  ● Problem: b ​ ecause this requires the same test to be  administered twice to an individual, the correlation might be  artificially high because the individuals remember how they  responded the first time  ■ Alternate forms reliability​ ­ requires administering two different  forms of the same test to the same individuals at two points in time  ● Drawback: creating a second equivalent measure may  require considerable time and effort  ○ Internal Consistency Reliability  ■ Internal consistency reliability​ ­ the assessment of reliability  using responses at only one point in time  ● All items measure the same variable, so they should yield  similar or consistent results  ■ Split­half reliability​ ­ the correlation of the total score on one half  of the test with the total score on the other half  ● The two halves are created by randomly dividing the items  into two parts  ● Final measure will include items from both halves = more  items = more reliable than either half by itself  ○ This fact must be taken into account when calculating  the reliability coefficie​ Spearman­Brown split­half  reliability coefficient)  ● Downside: based on only one of many possible ways of  dividing the measure into halves  ■ Cronbach’s alpha​ ​­ provides us with the average of all possible  split­half reliability coefficients  ● Scores on each item are correlated with scores on every  other item  ● Based on the average of all the inter­item correlation  coefficients and the number of items in the measure  ● More items = higher reliability  ■  ​Item­total correlations​ ­ very informative; provide information  about each individual item  ● Examines the correlation of each item score with the total  based on all items  ● Items that do not correlate with the total score on the  measure are actually measuring a different variable ­> can  be eliminated to increase internal consistency reliability  ○ Interrater Reliability  ■ To make a rating or judgment, a rater uses instructions for making  judgements  ■ The single observations of one rater might be unreliable  ■ Interrater reliability​ ­ the extent to which raters agree in their  observations  ■ Cohen’s kappa​ ­ commonly used indicator of interrater reliability  ○ Reliability and Accuracy of Measures  ■ Reliability does not tell us about whether we have a good measure  of the variable of interest  ■ The difference between the reliability and accuracy of  measurements leave us the consideration of validity of  measures  ● Construct Validity of Measures  ○ Construct validity​ ­ concerns whether our methods of studying variables  are accurate; adequacy of the operational definition of variables; in terms  of measurement: a question of whether the measure that is employed  actually measures the construct it is intended to measure  ○ Indicators of Construct Validity  ■ Face Validity  ● Face validity  ​ ­ the degree to which something measures  what it is supposed to measure  ● Not very sophisticated ­ only involves a judgment of whether,  given the theoretical definition of the variable, the content of  the measure appears to actually measure the variable  ● Not sufficient to conclude that a measure is valid  ■ Content Validity  ● Content validity​ ­ ​   based on comparing the content of the  measure with the universe of content that define the  constructs   ■ Predictive Validity  ● Predictive validity​ ­ research that uses a measure to  predict some future behavior  ● Criterion is based on future behavior or outcomes  ● Important when studying measures that are designed to  improve our ability to make predictions  ■ Concurrent Validity  ● Concurrent validity  ​ ­ demonstrated by research that  examines the relationship between the measure and a  criterion behavior at the same time (concurrently)  ● Can take on many forms  ● A common method is to study whether two or more groups  of people differ on the measure in expected ways  ● Another approach is to study how people who score either  low or high on the measure behave in different situations  ■ Convergent Validity  ● Convergent validity​ ­ the extent to which scores on the  measure in question are related to scores on other  measures of the same construct or similar constructs  ● Measures of similar constructs should converge  ■ Discriminant Validity  ● Discriminant validity  ​ ­ demonstrated when the measure is  not related to variables when it should be related  ● Reactivity of Measures  ○ Reactivity​ ­ awareness of being measured changes an individual’s  behavior  ○ A reactive measure tells us what the person is like when he or she is  aware of being observed ­ does not tell how a person would behave under  natural circumstances  ○ Measures of behavior vary in terms of their potential reactivity  ○ There are ways to minimize reactivity  ■ Ex. allowing time for individuals to become used to the presence of  the observer or recording equipment  ● Variables and Measurement Scales  ○ Nominal Scales  ■ Nominal scales​ ­ categories with no numeric scales  ● Ex. males and females  ■ You can assign numbers, but they would be meaningless, except  for identification  ■ The independent variables is often a nominal/categorical variable  ○ Ordinal Scales  ■ Ordinal scales​ ­ allow us to rank order the levels of the variable  being studied  ■ Categories can be ordered from first to last  ● Ex. letter grades ­> categories that can be organized in a  meaningful way A B C D F  ■ Not a nominal scale   ○ Interval and Ratio Scales  ■ Interval scale​ ­ the difference between the numbers on the scale is  meaningful; numeric properties are literal  ● The intervals between the numbers are equal in size  ● Ex. thermometer measures temperature on an interval scale  ● The zero on any interval scale is only an arbitrary reference  point ­> there is no absolute zero  ■ Ratio scales​ ­ do have an absolute zero point that indicates the  absence of the variable being measured  ● Used when variables involve physical measures being  studied  ● Ex. length, weight, time   


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