Question 1

In 1904, Charles Spearman published one of the most important papers in the history of psychology in which he described a latent variable. What was it?

Accepted Answer

A)  General Intelligence. 
B)  The "Big Five". 
C)  Self-Esteem. 
D)  Depression 
A)  General Intelligence. 
B)  The "Big Five". 
C)  Self-Esteem. 
D)  Depression A

Question 2

Researchers were interested in identifying the number of factors underlying a 6 item survey. The factor loadings are given below. How would you characterize the loadings on the second factor?
             factor matrixa                      factor               1       2               X1       -.890       .023               X2       -.740       .111               X3       -.732       .097               X4       .004       .854               X5       .009       .900               X6       .120       .831

Accepted Answer

A)  The second factor was characterized by near-zero loadings from items X1, X2, and X3 and weak positive loadings from items X4, X5, and X6. 
B)  The second factor was characterized by strong negative loadings from items X1, X2, and X3 and near-zero loadings from items X4, X5, and X6. 
C)  The second factor was characterized by near-zero loadings from items X1, X2, and X3 and strong positive loadings from items X4, X5, and X6. 
D)  The second factor was characterized by moderate positive loadings from X1, X2, and X3 and moderate negative loadings from items X4, X5, and X6. 
A)  The second factor was characterized by near-zero loadings from items X1, X2, and X3 and weak positive loadings from items X4, X5, and X6. 
B)  The second factor was characterized by strong negative loadings from items X1, X2, and X3 and near-zero loadings from items X4, X5, and X6. 
C)  The second factor was characterized by near-zero loadings from items X1, X2, and X3 and strong positive loadings from items X4, X5, and X6. 
D)  The second factor was characterized by moderate positive loadings from X1, X2, and X3 and moderate negative loadings from items X4, X5, and X6. C

Question 3

Paul was interested in how associated a whole set of 7 quiz items was. He calculated the median lors for each of the quiz items with each question removed. The results are shown below:
$$\begin{array} { | l | l | l | l | l | l | l | } 
\hline ? & \text { w/o } & \text { w/o } & \text { w/o } & \text { w/o } & \text { w/o } & \text { w/o } \
& \mathrm { Q } 2 & \mathrm { Q } 3 & \mathrm { Q } 4 & \mathrm { Q } 5 & \text { Q6 } & \text { Q7 } \
\hline 0.87 & 0.79 & 1.35 & 0.95 & 0.68 & 0.81 & 0.51 \
\hline
\end{array}$$ On the basis of the results, which question (if any) may Janet wish to remove from her data?

Accepted Answer

A)  Question 5 
B)  Question 7 
C)  Question 3 
D)  None 
A)  Question 5 
B)  Question 7 
C)  Question 3 
D)  None C

Question 4

Calculate the 95% confidence interval for lor calculated in Item 6. Remember to include a starting value of 0.5.

Accepted Answer

A)  F1F1F1S1F1F1F10 F1F1F1S1F1F1F10 1.86, 1.64 
B)  F1F1F1S1F1F1F10 F1F1F1S1F1F1F10 2.88, 3.61 
C)  F1F1F1S1F1F1F10 3.00, 0.78 
D)  F1F1F1S1F1F1F10 F1F1F1S1F1F1F10 1.96, F1F1F1S1F1F1F10 1.74 
A)  F1F1F1S1F1F1F10 F1F1F1S1F1F1F10 1.86, 1.64 
B)  F1F1F1S1F1F1F10 F1F1F1S1F1F1F10 2.88, 3.61 
C)  F1F1F1S1F1F1F10 3.00, 0.78 
D)  F1F1F1S1F1F1F10 F1F1F1S1F1F1F10 1.96, F1F1F1S1F1F1F10 1.74

Question 5

Calculate the log-odds ratio between Question 1 and Question 5 given the data below. Be sure to add a starting value of .50.
                           Q5                                    WRONG      RIGHT        ROW TOTAL              Q1        WRONG       3       4       7               RIGHT       6       7       13                      Column total       9       11       20

Accepted Answer

A)  F1F1F1S1F1F1F10 0.50 
B)  F1F1F1S1F1F1F10 0.88 
C)  F1F1F1S1F1F1F10 F1F1F1S1F1F1F10 0.11 
D)  F1F1F1S1F1F1F10 F1F1F1S1F1F1F10 1.13 
A)  F1F1F1S1F1F1F10 0.50 
B)  F1F1F1S1F1F1F10 0.88 
C)  F1F1F1S1F1F1F10 F1F1F1S1F1F1F10 0.11 
D)  F1F1F1S1F1F1F10 F1F1F1S1F1F1F10 1.13

Question 6

Based on Catell's scree method, how many factors should you retain in this unrotated EFA solution?

Accepted Answer

A)  4 
B)  6 
C)  2 
D)  3 
A)  4 
B)  6 
C)  2 
D)  3

Question 7

Based on the factor loadings given below, how many factors would you retain from this exploratory factor analysis?
             factor matrixa                      factor               1       2               X1      .769      .131               X2      .700      .173               X3      .011      .793               X4      .003      .812               X5      .937      -.001               X6      .132      .783

Accepted Answer

A)  2 
B)  0 
C)  1 
D)  4 
A)  2 
B)  0 
C)  1 
D)  4

Question 8

John administered a 3 item depression questionnaire to 50 students. He was interested in assessing the reliability of his instrument. He returned a Cronbach's α of .29. He was concerned that this was low. Which of these might account for the small α ?

Accepted Answer

A)  The sample size used. 
B)  The number of items on the questionnaire. 
C)  The researcher's bias. 
D)  How missing values were imputed. 
A)  The sample size used. 
B)  The number of items on the questionnaire. 
C)  The researcher's bias. 
D)  How missing values were imputed.

Question 9

When dealing with latent variable data, what is NOT something of concern when it comes to making inferences?

Accepted Answer

A)  The complexity of the questions. 
B)  When the scores are high stakes. 
C)  Bad test questions. 
D)  All of these. 
A)  The complexity of the questions. 
B)  When the scores are high stakes. 
C)  Bad test questions. 
D)  All of these.

Question 10

When using the Fisher's r→z transformation to make confidence intervals, after you calculate the bounds for the z variables, you should remember to:

Accepted Answer

A)  Transform these back into r values. 
B)  Multiply all values by the log of 1. 
C)  Divide by the square root of the sample size. 
D)  Multiply by the square root of the sample size. 
A)  Transform these back into r values. 
B)  Multiply all values by the log of 1. 
C)  Divide by the square root of the sample size. 
D)  Multiply by the square root of the sample size.

Question 11

A latent variable differs from a manifest variables in that:

Accepted Answer

A)  they are not binary. 
B)  they are hidden and therefore don't exert an effect. 
C)  they are unobservable. 
D)  they are interval level variables. 
A)  they are not binary. 
B)  they are hidden and therefore don't exert an effect. 
C)  they are unobservable. 
D)  they are interval level variables.

Question 12

When is IRT preferred over EFA?

Accepted Answer

A)  When using binary latent variables. 
B)  When using binary manifest variables. 
C)  When using these are more than three latent variables. 
D)  When the latent variables are ordinal. 
A)  When using binary latent variables. 
B)  When using binary manifest variables. 
C)  When using these are more than three latent variables. 
D)  When the latent variables are ordinal.

Question 13

Why might IRT produce a more meaningful analysis of a student's ability versus just the percentage correct?

Accepted Answer

A)  Because it is much easier for the student to understand. 
B)  Because it does not use the scree plot. 
C)  Because the abilities are less affected by poor questions. 
D)  Because it will produce the same test score. 
A)  Because it is much easier for the student to understand. 
B)  Because it does not use the scree plot. 
C)  Because the abilities are less affected by poor questions. 
D)  Because it will produce the same test score.

Question 14

Marley got back her student's exams and found that 42% of the questions were not answered (i.e., left blank) by over half of the students. Which of the following should she investigate:

Accepted Answer

A)  that some of these questions were poorly written. 
B)  that there was not enough time to complete the test. 
C)  the content was not covered in class appropriately. 
D)  All of these. 
A)  that some of these questions were poorly written. 
B)  that there was not enough time to complete the test. 
C)  the content was not covered in class appropriately. 
D)  All of these.

Question 15

Barbara collected data from school leaders from all 300 schools in a large city. She collected data on 50 different average test scores and wanted to reduce the number of dimensions. What analysis method should she use?

Accepted Answer

A)  Principal Principal Components Analysis 
B)  Item Response Theory 
C)  Correlation matrix 
D)  Fisher's transformation Analysis. 
A)  Principal Principal Components Analysis 
B)  Item Response Theory 
C)  Correlation matrix 
D)  Fisher's transformation Analysis.

Question 16

When looking at the associations between two variables, you might consider all of the following except:

Accepted Answer

A)  Outliers 
B)  General trend 
C)  how large the means are 
D)  if one variable may cause the other 
A)  Outliers 
B)  General trend 
C)  how large the means are 
D)  if one variable may cause the other

Question 17

Based on your solution in item 6. Give an appropriate statement for the relationship between question 1 and question 5.

Accepted Answer

A)  If you got Question 1 right, you are more likely to get Question 5 right. 
B)  If you got Question 1 right, you are less likely to get Question 5 right. 
C)  If you got Question 5 right, you are less likely to get Question 1 wrong. 
D)  The questions are not appropriate for this age group. 
A)  If you got Question 1 right, you are more likely to get Question 5 right. 
B)  If you got Question 1 right, you are less likely to get Question 5 right. 
C)  If you got Question 5 right, you are less likely to get Question 1 wrong. 
D)  The questions are not appropriate for this age group.

Question 18

Researchers were interested in identifying the number of factors underlying a 6 item survey. The factor loadings are given below. How would you characterize the loadings on the first factor?
             factor matrixa                      factor               1       2               X1       -.890       .023               X2       -.740       .111               X3       -.732       .097               X4       .004       .854               X5       .009       .900               X6       .120       .831

Accepted Answer

A)  The first factor was characterized by near-zero loadings from items X1, X2, and X3 and weak positive loadings from items X4, X5, and X6. 
B)  The first factor was characterized by strong negative loadings from items X1, X2, and X3 and near-zero loadings from items X4, X5, and X6. 
C)  The first factor was characterized by near-zero loadings from items X1, X2, and X3 and strong positive loadings from items X4, X5, and X6. 
D)  The first factor was characterized by moderate positive loadings from X1, X2, and X3 and moderate negative loadings from items X4, X5, and X6. 
A)  The first factor was characterized by near-zero loadings from items X1, X2, and X3 and weak positive loadings from items X4, X5, and X6. 
B)  The first factor was characterized by strong negative loadings from items X1, X2, and X3 and near-zero loadings from items X4, X5, and X6. 
C)  The first factor was characterized by near-zero loadings from items X1, X2, and X3 and strong positive loadings from items X4, X5, and X6. 
D)  The first factor was characterized by moderate positive loadings from X1, X2, and X3 and moderate negative loadings from items X4, X5, and X6.

Question 19

Given the results of the EFA and SPSS Output below, about what percent of the common variance is explained by Factor 2?
             total variance explained               factor       initial eigenvalues       extraction sums of square loadings               total       % of variance      cumulative %         total        % of variance       cumulative %               1       2.162       36.035       36.035       1.692       28.201       28.201               2       1.885       31.414       67.449       1.389       23.142       51.343               3       .566       9.425       76.875                                    4       .509       8.480      85.355                                   5       .471       7.842       93.197                                    6       .408       6.803       100.000

Accepted Answer

A)  67.5% 
B)  31.4% 
C)  36% 
D)  9.43% 
A)  67.5% 
B)  31.4% 
C)  36% 
D)  9.43%

Question 20

Why would you add a starting value to each cell of your data before calculating log-odds ratios?

Accepted Answer

A)  It heightens the effects of any cells with low frequencies. 
B)  It lessens the effects of any cells with low frequencies. 
C)  It heightens the effects of cells with large numbers of missing data. 
D)  It lessens the effects of cells with large numbers of missing data. 
A)  It heightens the effects of any cells with low frequencies. 
B)  It lessens the effects of any cells with low frequencies. 
C)  It heightens the effects of cells with large numbers of missing data. 
D)  It lessens the effects of cells with large numbers of missing data.

In 1904, Charles Spearman published one of the most important papers in the history of psychology in which he described a latent variable. What was it?

Calculate the 95% confidence interval for lor calculated in Item 6. Remember to include a starting value of 0.5.

Calculate the log-odds ratio between Question 1 and Question 5 given the data below. Be sure to add a starting value of .50.

Q5

WRONG RIGHT ROW TOTAL

Q1 WRONG 3 4 7

RIGHT 6 7 13

Column total 9 11 20

Based on Catell's scree method, how many factors should you retain in this unrotated EFA solution?

Based on the factor loadings given below, how many factors would you retain from this exploratory factor analysis?

factor matrix^a

factor

1 2

X1 .769 .131

X2 .700 .173

X3 .011 .793

X4 .003 .812

X5 .937 -.001

X6 .132 .783

John administered a 3 item depression questionnaire to 50 students. He was interested in assessing the reliability of his instrument. He returned a Cronbach's α of .29. He was concerned that this was low. Which of these might account for the small α ?

When dealing with latent variable data, what is NOT something of concern when it comes to making inferences?

When using the Fisher's r→z transformation to make confidence intervals, after you calculate the bounds for the z variables, you should remember to:

A latent variable differs from a manifest variables in that:

When is IRT preferred over EFA?

Why might IRT produce a more meaningful analysis of a student's ability versus just the percentage correct?

Marley got back her student's exams and found that 42% of the questions were not answered (i.e., left blank) by over half of the students. Which of the following should she investigate:

Barbara collected data from school leaders from all 300 schools in a large city. She collected data on 50 different average test scores and wanted to reduce the number of dimensions. What analysis method should she use?

When looking at the associations between two variables, you might consider all of the following except:

Based on your solution in item 6. Give an appropriate statement for the relationship between question 1 and question 5.

Why would you add a starting value to each cell of your data before calculating log-odds ratios?

Research Questions, Design, Strategy and Choice of Methods

Ethics

Big Questions and New Methods

Capturing and Recording Information

Telling Others About Your Research

Psychology As a Science: What Is Science

Accessing Difficult to Access Information

Quasi-Experimental Designs Including Obervational Methods

Experimental Design

Interviewing and Focus Groups

Descriptive Statistics: Graphical and Numerical Methods

Content Analysis, Thematic Analysis and Discourse Analysis

Self-Report Data

Questionnaire Design

Surveys and Sampling

Inferential Statistics

Factorial Anova

Correlation and Regression

Filters

factor matrix^a
	factor
	1	2
X1	-.890	.023
X2	-.740	.111
X3	-.732	.097
X4	.004	.854
X5	.009	.900
X6	.120	.831

factor matrix^a
	factor
	1	2
X1	.769	.131
X2	.700	.173
X3	.011	.793
X4	.003	.812
X5	.937	-.001
X6	.132	.783

total variance explained
factor	initial eigenvalues			extraction sums of square loadings
factor	total	% of variance	cumulative %	total	% of variance	cumulative %
1	2.162	36.035	36.035	1.692	28.201	28.201
2	1.885	31.414	67.449	1.389	23.142	51.343
3	.566	9.425	76.875
4	.509	8.480	85.355
5	.471	7.842	93.197
6	.408	6.803	100.000

Exam 19: Creating Latent Variables

In 1904, Charles Spearman published one of the most important papers in the history of psychology in which he described a latent variable. What was it?

Researchers were interested in identifying the number of factors underlying a 6 item survey. The factor loadings are given below. How would you characterize the loadings on the second factor? factor matrixa factor 1 2 X1 -.890 .023 X2 -.740 .111 X3 -.732 .097 X4 .004 .854 X5 .009 .900 X6 .120 .831

Calculate the 95% confidence interval for lor calculated in Item 6. Remember to include a starting value of 0.5.

Calculate the log-odds ratio between Question 1 and Question 5 given the data below. Be sure to add a starting value of .50. Q5 WRONG RIGHT ROW TOTAL Q1 WRONG 3 4 7 RIGHT 6 7 13 Column total 9 11 20

Based on Catell's scree method, how many factors should you retain in this unrotated EFA solution?

Based on the factor loadings given below, how many factors would you retain from this exploratory factor analysis? factor matrixa factor 1 2 X1 .769 .131 X2 .700 .173 X3 .011 .793 X4 .003 .812 X5 .937 -.001 X6 .132 .783

John administered a 3 item depression questionnaire to 50 students. He was interested in assessing the reliability of his instrument. He returned a Cronbach's α of .29. He was concerned that this was low. Which of these might account for the small α ?

When dealing with latent variable data, what is NOT something of concern when it comes to making inferences?

When using the Fisher's r→z transformation to make confidence intervals, after you calculate the bounds for the z variables, you should remember to:

A latent variable differs from a manifest variables in that:

When is IRT preferred over EFA?

Why might IRT produce a more meaningful analysis of a student's ability versus just the percentage correct?

Marley got back her student's exams and found that 42% of the questions were not answered (i.e., left blank) by over half of the students. Which of the following should she investigate:

Barbara collected data from school leaders from all 300 schools in a large city. She collected data on 50 different average test scores and wanted to reduce the number of dimensions. What analysis method should she use?

When looking at the associations between two variables, you might consider all of the following except:

Based on your solution in item 6. Give an appropriate statement for the relationship between question 1 and question 5.

Researchers were interested in identifying the number of factors underlying a 6 item survey. The factor loadings are given below. How would you characterize the loadings on the first factor? factor matrixa factor 1 2 X1 -.890 .023 X2 -.740 .111 X3 -.732 .097 X4 .004 .854 X5 .009 .900 X6 .120 .831

Why would you add a starting value to each cell of your data before calculating log-odds ratios?

Research Questions, Design, Strategy and Choice of Methods

Ethics

Big Questions and New Methods

Capturing and Recording Information

Telling Others About Your Research

Psychology As a Science: What Is Science

Accessing Difficult to Access Information

Quasi-Experimental Designs Including Obervational Methods

Experimental Design

Interviewing and Focus Groups

Descriptive Statistics: Graphical and Numerical Methods

Content Analysis, Thematic Analysis and Discourse Analysis

Self-Report Data

Questionnaire Design

Surveys and Sampling

Inferential Statistics

Factorial Anova

Correlation and Regression

Filters

Calculate the log-odds ratio between Question 1 and Question 5 given the data below. Be sure to add a starting value of .50.

Q5

WRONG RIGHT ROW TOTAL

Q1 WRONG 3 4 7

RIGHT 6 7 13

Column total 9 11 20

Based on the factor loadings given below, how many factors would you retain from this exploratory factor analysis?

factor matrix^a

factor

1 2

X1 .769 .131

X2 .700 .173

X3 .011 .793

X4 .003 .812

X5 .937 -.001

X6 .132 .783