AMCP (version 2.0.0)

chapter_16_table_4: The data used in Chapter 16, Table 4

Description

The data used in Chapter 16, Table 4

Usage

data(chapter_16_table_4)

Format

An object of class data.frame with 29 rows and 6 columns.

Variables

Observation

observation/participant number

Room

participant classroom placement

Condition

participant condition (0=control, 1=treatment)

Cognition

participant cognitive ability score

Skill

participant's teacher's teaching skill

Inductive

induction; scores on the dependent variable

Synonym

C16T4

Author

Ken Kelley

Details

The hypothetical data contained in Table 16.4 is supposed to represent the data from 29 children who participated in a study to evaluate the effectiveness of an intervention designed to increase inductive reasoning skills. The data consists of children who are nested within one of six classrooms, where each classroom contained students from both the control and the experimental condition. The question of interest is whether or not the children who participated in the experimental group actually improved their cognitive reasoning ability.

The children with condition values of 0 received the control, whereas the 14 children with condition values of 1 received the treatment. 4 of the children in the control condition were students in control Classroom 1, 6 of them were students in control Classroom 2, and 5 were students in control Classroom 3. Similarly, 3 of the students in the treatment condition were students in treatment Classroom 1, 5 were students in treatment Classroom 2, and 6 were students in treatment Classroom 3. It is also important to note that scores on the dependent variable appear in the rightmost column under the variable label "induct". The variable labeled "cog" in Table 16.4 represents cognitive ability scores that have been obtained for each student sometime prior to assigning classrooms to treatment conditions. The variable labeled "skill" represents a global measure of each teacher's teaching skill, once again assigned prior to assigning classrooms to treatment conditions.

References

Maxwell, S. E., Delaney, H. D., & Kelley, K. (2027). Designing experiments and analyzing data: A model comparison perspective (4th ed.). New York, NY: Routledge.

Examples

# Load the data
data(chapter_16_table_4)

# Or, alternatively load the data as
data(C16T4)

# View the structure
str(chapter_16_table_4)

# ---------------------------------------------------------------------
# Optional: a factor-coded copy for model-comparison analyses / plotting.
# Condition and Room are stored as numeric codes so the book's examples
# reproduce exactly. Build a *copy* (suffix "_factors") so the canonical
# data set is left unchanged; Cognition, Skill, and Inductive stay
# numeric. Labels for Condition are taken from the description above
# (0 = control, 1 = treatment); Room (classroom) is a nesting id, so its
# numeric codes are kept as levels.
C16T4_factors <- chapter_16_table_4
C16T4_factors$Condition <- factor(C16T4_factors$Condition, levels = 0:1,
  labels = c("Control", "Treatment"))
C16T4_factors$Room <- factor(C16T4_factors$Room)

# These data come from a nested / mixed-effects design (children within
# classrooms); the book fits the appropriate multilevel model. Build the
# factor copy, then follow the book's procedure.
str(C16T4_factors)