chapter_13_table_12 {AMCP} R Documentation

## The data used in Chapter 13, Table 12

### Description

The data used in Chapter 13, Table 12

The data used in Chapter 13, Table 12

### Usage

```data(chapter_13_table_12)

data(chapter_13_table_12)
```

### Format

An object of class `data.frame` with 8 rows and 2 columns.

An object of class `data.frame` with 8 rows and 2 columns.

### Details

For the hypothetical data contained in Table 13.2, the linear and quadratic D variables were formed by making use of the appropriate coefficients from Appendix Table A.10. Because the eight participants were measured at three occasions, both a linear and a quadratic effect can be tested. The question of interest in this instance is: "is there a linear and/or quadratic trend exhibited by the group over time?" Recall that in the book (pages 646-647) it was shown that the D variables for linear and quadratic effects led to an omnibus F test of 19.148, which was a value previously obtained for the omnibus effect. Because the particular values chosen for the D variables do not matter (unless it leads to a linear combination of columns), we will focus only on the tests of the individual contrasts when analyzing the data given in Table 12. Because columns one and two already represent the linear and quadratic effect respectively, all that needs to be done is to test mean of the column in order to determine if it differs from zero.

Table 13.14 shows the slope of the least-squares regression line for each of the eight subjects, as well as the score on the linear D variable, reproduced from Table 13.12. There is a strikin relationship between the numbers in the two columns of Table 13.14. Every subject's score on D is 24 times his or her slope.

### Variables

months30

hypothetical McCarthy IQ for 30-month-old individuals

months36

hypothetical McCarthy IQ for 36-month-old individuals

months42

hypothetical McCarthy IQ for 42-month-old individuals

months48

hypothetical McCarthy IQ for 48-month-old individuals

slope

slope of the least-squares regression line for data in Table 13.2

linear

Linear D variable for data in Table 13.2

C13T12

C13T12

### Author(s)

Ken Kelley kkelley@nd.edu

Ken Kelley kkelley@nd.edu

### Source

Maxwell, S. E., Delaney, H. D., & Kelley, K. (2018). Designing experiments and analyzing data: A model comparison perspective. (3rd ed.). New York, NY: Routledge.

Maxwell, S. E., Delaney, H. D., & Kelley, K. (2018). Designing experiments and analyzing data: A model comparison perspective. (3rd ed.). New York, NY: Routledge.

### References

Maxwell, S. E., Delaney, H. D., \& Kelley, K. (2018). Designing experiments and analyzing data: A model comparison perspective (3rd ed.). New York, NY: Routledge.

Maxwell, S. E., Delaney, H. D., \& Kelley, K. (2018). Designing experiments and analyzing data: A model comparison perspective (3rd ed.). New York, NY: Routledge.

### Examples

```# Load the data
data(chapter_13_table_12)

# Or, alternatively load the data as
data(C13T12)

# View the structure
str(chapter_13_table_12)

# Load the data
data(chapter_13_table_12)

# Or, alternatively load the data as
data(C13T12)

# View the structure
str(chapter_13_table_12)

```

[Package AMCP version 1.0.1 Index]