Type: Package
Title: Single-Case Randomization Tests
Version: 1.3.1
Date: 2019-12-20
Depends: R (≥ 2.14.1)
Imports: graphics, utils
Author: Isis Bulte, Tamal Kumar De, Patrick Onghena
Maintainer: Tamal Kumar De <tamalkumar.de@kuleuven.be>
Description: Design single-case phase, alternation and multiple-baseline experiments, and conduct randomization tests on data gathered by means of such designs, as discussed in Bulte and Onghena (2013) <doi:10.22237/jmasm/1383280020>.
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
Repository: CRAN
NeedsCompilation: no
Packaged: 2019-12-20 19:35:50 UTC; Tamal
Date/Publication: 2020-01-09 05:40:08 UTC

Single-Case Randomization Tests

Description

Design single-case phase, alternation and multiple-baseline experiments, and conduct randomization tests on data gathered by means of such designs.

Details

Package: SCRT
Type: Package
Version: 1.3.1
Date: 2019-12-20
License: GPL version 2 or newer

Author(s)

Isis Bulte, Tamal Kumar De, Patrick Onghena

Maintainer: Tamal Kumar De <tamalkumar.de@kuleuven.be>

Hypothetical ABAB data

Description

Hypothetical data from Onghena (1992), collected in an ABAB design with 24 measurement times.

Usage

data(ABAB)

Format

A data frame with 24 observations.

Source

Onghena, P. (1992). Randomization tests for extensions and variations of AB single-case experimental designs: A rejoinder. Behavioral Assessment, 14, 153-171.

References

Bulte, I., & Onghena, P. (2008). An R package for single-case randomization tests. Behavior Research Methods, 40, 467-478.

Examples

data(ABAB)

All assignments possibilities

Description

All assignment possibilities for the specified design are enumerated.

Usage

assignments(design, save = "no", MT, limit, 
starts = file.choose(new = FALSE), assignments = file.choose(new = FALSE))

Arguments

design

Type of single-case design: "AB", "ABA", "ABAB", "CRD" (completely randomized design), "RBD" (randomized block design), "ATD" (alternating treatments design), "MBD" (multiple-baseline AB design) or "Custom" (user specified design).

save

Save the possible assignments to a file (save="yes") or just see them as output in the R console (default: save="no").

MT

Measurement times: number of observations.

limit

For phase designs: minimum number of observations per phase. For alternating treatments designs: maximum number of consecutive administrations of the same condition.

starts

Only for multiple baseline designs: location of the file where the possible start points can be found. Default: a window pops up in which the file can be selected.

assignments

Only for user specified designs: location of the file where all the possible assignments can be found. Default: a window pops up in which the file can be selected.

Details

When choosing to save the possible assignments to a file, a window will pop up (for multiple baseline designs or user specified designs this is the second pop-up window!!!) to ask where to save them. This location can be an existing file, as well as a new file that can be created by giving a file name and the extension .txt. In this latter case a confirmation is required ("The file does not exist yet. Create the file?").

For multiple baseline designs, when using the default starts argument, first a window pops up in which is asked in what file the possible start points can be found. In this startpoint file, each row should contain all possibilities for one unit, separated by a tab. The rows and columns should not be labeled.

For user specified designs, when using the default assignments argument, first a window pops up in which is asked in what file all the possible assignments can be found. In this file, each row should contain the sequence of conditions in one possible assignment, separated by a tab. There should be one row for every possible assignment. The rows and columns should not be labeled.

For multiple baseline designs, the possible combinations of start points for each unit are returned. There may be duplicates among these assignments if there are overlaps between the start points for different subjects, this is a result of the subjects also being randomized to the set of start points.

For all other designs, the possible sequences of conditions are returned (e.g., "A" "A" "A" "A" "B" "B" "B").

References

Bulte, I., & Onghena, P. (2008). An R package for single-case randomization tests. Behavior Research Methods, 40, 467-478.

Bulte, I., & Onghena, P. (2009). Randomization tests for multiple baseline designs: An extension of the SCRT-R package. Behavior Research Methods, 41, 477-485.

http://ppw.kuleuven.be/home/english/research/mesrg

See Also

quantity to calculate the number of assignment possibilities.

selectdesign to randomly select one of the assignment possibilities.

Examples

assignments(design = "ABAB", save = "no", MT = 24, limit = 4)

Nonexhaustive randomization distribution

Description

The nonexhaustive randomization distribution is generated by a random sample of all assignment possibilities.

Usage

distribution.random(design, statistic, save = "no", 
number, limit, data = read.table(file.choose(new = FALSE)), 
starts = file.choose(new = FALSE), assignments = file.choose(new = FALSE))

Arguments

design

Type of single-case design: "AB", "ABA", "ABAB", "CRD" (completely randomized design), "RBD" (randomized block design), "ATD" (alternating treatments design), "MBD" (multiple-baseline AB design) or "Custom" (user specified design).

statistic

Test statistic. For alternation designs, multiple-baseline designs and AB phase designs, there are 3 built-in possibilities: "A-B", "B-A", and "|A-B|", which stand for the (absolute value of the) difference between condition means. For phase designs with more than 2 phases, 3 more built-in options are available: "PA-PB", "PB-PA", and "|PA-PB|" refer to the (absolute value of the) difference between the means of phase means. Additionally, it is possible to specify a custom test statistic using the variable identifiers "A" and "B" (or in the case of phase deisgns with more than 2 phases, "A1", "B1", "A2", "B2", "A" and "B") and any of the basic R functions. For example, "abs(mean(A) - mean(B))" can be used as a test statistic and it will be the same as using "|A-B|".

save

Save the randomization distribution to a file (save="yes") or just see it as output in the R console (default: save="no").

number

Number of randomizations required. Please note that the observed test statistic is always included in the randomization distribution.

limit

For phase designs: minimum number of observations per phase. For alternating treatments designs: maximum number of consecutive administrations of the same condition.

data

File in which the data can be found. Default: a window pops up in which the file can be selected.

starts

Only for multiple baseline designs: location of the file where the possible start points can be found. Default: a window pops up in which the file can be selected.

assignments

Only for user specified designs: location of the file where all the possible assignments can be found. Default: a window pops up in which the file can be selected.

Details

When using the default data argument, a window will pop up to ask in what file the data can be found. This text file containing the data should consist of two columns for single-case phase and alternation designs: the first with the condition labels and the second with the obtained scores. For multiple-baseline designs it should consist of these two columns for EACH unit. This way, each row represents one measurement occasion. It is important not to label the rows or columns.

For multiple baseline designs, when using the default starts argument, second a window pops up in which is asked in what file the possible start points can be found. In this startpoint file, each row should contain all possibilities for one unit, separated by a tab. The rows and columns should not be labeled.

For user specified designs, when using the default assignments argument, second a window pops up in which is asked in what file all the possible assignments can be found. In this file, each row should contain the sequence of conditions in one possible assignment, separated by a tab. There should be one row for every possible assignment. The rows and columns should not be labeled.

Missing data should be indicated as NA. When there is missing data, randomization distribution is generated as usual, but instead of randomly reshuffling numerical scores only, the missing data markers (NA) are also included in the reshuffling. For test statistic calculations, missing data are omitted.

When choosing to save the randomization distribution to a file, next a window will pop up (for multiple baseline designs or user specified designs this is the third pop-up window, for all other designs it is the second window) to ask where to save it. This location can be an existing file, as well as a new file that can be created by giving a file name and the extension .txt. In this latter case a confirmation is required ("The file does not exist yet. Create the file?").

References

Bulte, I., & Onghena, P. (2008). An R package for single-case randomization tests. Behavior Research Methods, 40, 467-478.

Bulte, I., & Onghena, P. (2009). Randomization tests for multiple baseline designs: An extension of the SCRT-R package. Behavior Research Methods, 41, 477-485.

Edgington, E.S., & Onghena, P. (2007). Randomization Tests (4th ed.). Boca Raton, FL: Chapman & Hall/CRC.

Hope, A.C.A. (1968). A simplified Monte Carlo significance test procedure. Journal of the Royal Statistical Society, Series B 30, 582-598.

Onghena, P. & May, R.B. (1995). Pitfalls in computing and interpreting randomization test p values: A commentary on Chen and Dunlap. Behavior Research Methods, Instruments, & Computers, 27, 408-411.

http://ppw.kuleuven.be/home/english/research/mesrg

See Also

pvalue.random to obtain the corresponding p-value for the nonexhaustive randomization distribution.

observed to calculate the observed test statistic.

distribution.systematic to generate the exhaustive randomization distribution and pvalue.systematic to obtain the corresponding p-value.

Examples

data(ABAB)
distribution.random(design = "ABAB", statistic = "PA-PB", save = "no", 
number = 100, limit = 4, data = ABAB)

Exhaustive randomization distribution

Description

The exhaustive randomization distribution is generated by a complete enumeration of all assignment possibilities.

Usage

distribution.systematic(design, statistic, save = "no", 
limit, data = read.table(file.choose(new = FALSE)), 
starts = file.choose(new = FALSE), assignments = file.choose(new = FALSE))

Arguments

design

Type of single-case design: "AB", "ABA", "ABAB", "CRD" (completely randomized design), "RBD" (randomized block design), "ATD" (alternating treatments design), "MBD" (multiple-baseline AB design) or "Custom" (user specified design).

statistic

Test statistic. For alternation designs, multiple-baseline designs and AB phase designs, there are 3 built-in possibilities: "A-B", "B-A", and "|A-B|", which stand for the (absolute value of the) difference between condition means. For phase designs with more than 2 phases, 3 more built-in options are available: "PA-PB", "PB-PA", and "|PA-PB|" refer to the (absolute value of the) difference between the means of phase means. Additionally, it is possible to specify a custom test statistic using the variable identifiers "A" and "B" (or in the case of phase deisgns with more than 2 phases, "A1", "B1", "A2", "B2", "A" and "B") and any of the basic R functions. For example, "abs(mean(A) - mean(B))" can be used as a test statistic and it will be the same as using "|A-B|".

save

Save the randomization distribution to a file (save="yes") or just see it as output in the R console (default: save="no").

limit

For phase designs: minimum number of observations per phase. For alternating treatments designs: maximum number of consecutive administrations of the same condition.

data

File in which the data can be found. Default: a window pops up in which the file can be selected.

starts

Only for multiple baseline designs: location of the file where the possible start points can be found. Default: a window pops up in which the file can be selected.

assignments

Only for user specified designs: location of the file where all the possible assignments can be found. Default: a window pops up in which the file can be selected.

Details

When using the default data argument, a window will pop up to ask in what file the data can be found. This text file containing the data should consist of two columns for single-case phase and alternation designs: the first with the condition labels and the second with the obtained scores. For multiple-baseline designs it should consist of these two columns for EACH unit. This way, each row represents one measurement occasion. It is important not to label the rows or columns.

For multiple baseline designs, when using the default starts argument, second a window pops up in which is asked in what file the possible start points can be found. In this startpoint file, each row should contain all possibilities for one unit, separated by a tab. The rows and columns should not be labeled.

For user specified designs, when using the default assignments argument, second a window pops up in which is asked in what file all the possible assignments can be found. In this file, each row should contain the sequence of conditions in one possible assignment, separated by a tab. There should be one row for every possible assignment. The rows and columns should not be labeled.

Missing data should be indicated as NA. When there is missing data, randomization distribution is generated as usual, but instead of randomly reshuffling numerical scores only, the missing data markers (NA) are also included in the reshuffling. For test statistic calculations, missing data are omitted.

When choosing to save the randomization distribution to a file, next a window will pop up (for multiple baseline designs this is the third pop-up window, for all other designs it is the second window) to ask where to save it. This location can be an existing file, as well as a new file that can be created by giving a file name and the extension .txt. In this latter case a confirmation is required ("The file does not exist yet. Create the file?").

References

Bulte, I., & Onghena, P. (2008). An R package for single-case randomization tests. Behavior Research Methods, 40, 467-478.

Bulte, I., & Onghena, P. (2009). Randomization tests for multiple baseline designs: An extension of the SCRT-R package. Behavior Research Methods, 41, 477-485.

Edgington, E.S., & Onghena, P. (2007). Randomization Tests (4th ed.). Boca Raton, FL: Chapman & Hall/CRC.

http://ppw.kuleuven.be/home/english/research/mesrg

See Also

pvalue.systematic to obtain the corresponding p-value for the exhaustive randomization distribution.

observed to calculate the observed test statistic.

distribution.random to generate the nonexhaustive randomization distribution and pvalue.random to obtain the corresponding p-value.

Examples

data(ABAB)
distribution.systematic(design = "ABAB", statistic = "PA-PB", 
save = "no", limit = 4, data = ABAB)

Graphical representation of single-case data

Description

The observed single-case data are plotted.

Usage

graph1(design,data=read.table(file.choose(new=FALSE)),
xlab="Measurement Times",ylab="Scores")

Arguments

design

Type of single-case design: "AB", "ABA", "ABAB", "CRD" (completely randomized design), "RBD" (randomized block design), "ATD" (alternating treatments design), "MBD" (multiple-baseline AB design) or "Custom" (user specified design).

data

File in which the data can be found. Default: a window pops up in which the file can be selected.

xlab

Label x axis

ylab

Label y axis

Details

When using the default data argument, a window will pop up to ask in what file the data can be found. This text file containing the data should consist of two columns for single-case phase and alternation designs: the first with the condition labels and the second with the obtained scores. For multiple-baseline designs it should consist of these two columns for EACH unit. This way, each row represents one measurement occasion. It is important not to label the rows or columns.

For alternation designs, after the plot is drawn, the location of the legend should be indicated by a left mouse click.

Missing data should be indicated as NA. For calculations, missing data are omitted.

References

Bulte, I., & Onghena, P. (2008). An R package for single-case randomization tests. Behavior Research Methods, 40, 467-478.

Bulte, I., & Onghena, P. (2009). Randomization tests for multiple baseline designs: An extension of the SCRT-R package. Behavior Research Methods, 41, 477-485.

Bulte, I., & Onghena, P. (in press). When the Truth Hits You Between the Eyes: A Software Tool for the Visual Analysis of Single-Case Experimental Data. Manuscript accepted for publication in Methodology.

http://ppw.kuleuven.be/home/english/research/mesrg

Examples

data(ABAB)
graph1(design = "ABAB", data = ABAB)

Observed test statistic

Description

The observed test statistic is calculated from the obtained raw data.

Usage

observed(design, statistic, data = read.table(file.choose(new = FALSE)))

Arguments

design

Type of single-case design: "AB", "ABA", "ABAB", "CRD" (completely randomized design), "RBD" (randomized block design), "ATD" (alternating treatments design), "MBD" (multiple-baseline AB design) or "Custom" (user specified design).

statistic

Test statistic. For alternation designs, multiple-baseline designs and AB phase designs, there are 3 built-in possibilities: "A-B", "B-A", and "|A-B|", which stand for the (absolute value of the) difference between condition means. For phase designs with more than 2 phases, 3 more built-in options are available: "PA-PB", "PB-PA", and "|PA-PB|" refer to the (absolute value of the) difference between the means of phase means. Additionally, it is possible to specify a custom test statistic using the variable identifiers "A" and "B" (or in the case of phase deisgns with more than 2 phases, "A1", "B1", "A2", "B2", "A" and "B") and any of the basic R functions. For example, "abs(mean(A) - mean(B))" can be used as a test statistic and it will be the same as using "|A-B|".

data

File in which the data can be found. Default: a window pops up in which the file can be selected.

Details

When using the default data argument, a window will pop up to ask in what file the data can be found. This text file containing the data should consist of two columns for single-case phase and alternation designs: the first with the condition labels and the second with the obtained scores.

For multiple-baseline designs it should consist of these two columns for EACH unit. This way, each row represents one measurement occasion. It is important not to label the rows or columns.

Missing data should be indicated as NA. For calculations, missing data are omitted.

References

Bulte, I., & Onghena, P. (2008). An R package for single-case randomization tests. Behavior Research Methods, 40, 467-478.

Bulte, I., & Onghena, P. (2009). Randomization tests for multiple baseline designs: An extension of the SCRT-R package. Behavior Research Methods, 41, 477-485.

http://ppw.kuleuven.be/home/english/research/mesrg

See Also

distribution.systematic to generate the exhaustive randomization distribtion and pvalue.systematic to obtain the corresponding p-value.

distribution.random to generate the nonexhaustive randomization distribution and pvalue.random to obtain the corresponding p-value.

Examples

data(ABAB)
observed(design = "ABAB", statistic = "PA-PB", data = ABAB)

P-value using the Monte Carlo procedure

Description

The P-value corresponding to the observed value of the test statistic is obtained by locating this value in the randomization distribution generated by a random sample of all assignment possibilities (the nonexhaustive randomization distribution).

Usage

pvalue.random(design, statistic, save = "no", 
number, limit, data = read.table(file.choose(new = FALSE)), 
starts = file.choose(new = FALSE), assignments = file.choose(new = FALSE))

Arguments

design

Type of single-case design: "AB", "ABA", "ABAB", "CRD" (completely randomized design), "RBD" (randomized block design), "ATD" (alternating treatments design), "MBD" (multiple-baseline AB design) or "Custom" (user specified design).

statistic

Test statistic. For alternation designs, multiple-baseline designs and AB phase designs, there are 3 built-in possibilities: "A-B", "B-A", and "|A-B|", which stand for the (absolute value of the) difference between condition means. For phase designs with more than 2 phases, 3 more built-in options are available: "PA-PB", "PB-PA", and "|PA-PB|" refer to the (absolute value of the) difference between the means of phase means. Additionally, it is possible to specify a custom test statistic using the variable identifiers "A" and "B" (or in the case of phase deisgns with more than 2 phases, "A1", "B1", "A2", "B2", "A" and "B") and any of the basic R functions. For example, "abs(mean(A) - mean(B))" can be used as a test statistic and it will be the same as using "|A-B|".

save

Save the randomization distribution to a file (save="yes") or just see it as output in the R console (default: save="no").

number

Number of randomizations required. Please note that the observed test statistic is always included in the randomization distribution.

limit

For phase designs: minimum number of observations per phase. For alternating treatments designs: maximum number of consecutive administrations of the same condition.

data

File in which the data can be found. Default: a window pops up in which the file can be selected.

starts

Only for multiple baseline designs: location of the file where the possible start points can be found. Default: a window pops up in which the file can be selected.

assignments

Only for user specified designs: location of the file where all the possible assignments can be found. Default: a window pops up in which the file can be selected.

Details

When using the default data argument, a window will pop up to ask in what file the data can be found. This text file containing the data should consist of two columns for single-case phase and alternation designs: the first with the condition labels and the second with the obtained scores. For multiple-baseline designs it should consist of these two columns for EACH unit. This way, each row represents one measurement occasion. It is important not to label the rows or columns.

For multiple baseline designs, when using the default starts argument, second a window pops up in which is asked in what file the possible start points can be found. In this startpoint file, each row should contain all possibilities for one unit, separated by a tab. The rows and columns should not be labeled.

For user specified designs, when using the default assignments argument, second a window pops up in which is asked in what file all the possible assignments can be found. In this file, each row should contain the sequence of conditions in one possible assignment, separated by a tab. There should be one row for every possible assignment. The rows and columns should not be labeled.

Missing data should be indicated as NA. When there is missing data, randomization distribution is generated as usual, but instead of randomly reshuffling numerical scores only, the missing data markers (NA) are also included in the reshuffling. For test statistic calculations, missing data are omitted. If test statistic cannot be calculated for a particular randomization due to insufficient data for a treatment condition, the test statistic from this randomization is conservatively considered more extreme than the observed test statistic.

When choosing to save the randomization distribution to a file, next a window will pop up (for multiple baseline designs or user specified designs this is the third pop-up window, for all other designs it is the second window) to ask where to save it. This location can be an existing file, as well as a new file that can be created by giving a file name and the extension .txt. In this latter case a confirmation is required ("The file does not exist yet. Create the file?").

References

Bulte, I., & Onghena, P. (2008). An R package for single-case randomization tests. Behavior Research Methods, 40, 467-478.

Bulte, I., & Onghena, P. (2009). Randomization tests for multiple baseline designs: An extension of the SCRT-R package. Behavior Research Methods, 41, 477-485.

Edgington, E.S., & Onghena, P. (2007). Randomization Tests (4th ed.). Boca Raton, FL: Chapman & Hall/CRC.

Hope, A.C.A. (1968). A simplified Monte Carlo significance test procedure. Journal of the Royal Statistical Society, Series B 30, 582-598.

Onghena, P. & May, R.B. (1995). Pitfalls in computing and interpreting randomization test p values: A commentary on Chen and Dunlap. Behavior Research Methods, Instruments, & Computers, 27, 408-411.

http://ppw.kuleuven.be/home/english/research/mesrg

See Also

distribution.random to generate the corresponding nonexhaustive randomization distribution.

observed to calculate the observed test statistic.

distribution.systematic to generate the exhaustive randomization distribution and pvalue.systematic to obtain the corresponding p-value.

Examples

data(ABAB)
pvalue.random(design = "ABAB", statistic = "PA-PB", save = "no", 
number = 100, limit = 4, data = ABAB)

P-value using the systematic procedure

Description

The P-value corresponding to the observed value of the test statistic is obtained by locating this value in the randomization distribution generated by complete enumeration of all assignment possibilities (the exhaustive randomization distribution).

Usage

pvalue.systematic(design, statistic, save = "no", 
limit, data = read.table(file.choose(new = FALSE)), 
starts = file.choose(new = FALSE), assignments = file.choose(new = FALSE))

Arguments

design

Type of single-case design: "AB", "ABA", "ABAB", "CRD" (completely randomized design), "RBD" (randomized block design), "ATD" (alternating treatments design), "MBD" (multiple-baseline AB design) or "Custom" (user specified design).

statistic

Test statistic. For alternation designs, multiple-baseline designs and AB phase designs, there are 3 built-in possibilities: "A-B", "B-A", and "|A-B|", which stand for the (absolute value of the) difference between condition means. For phase designs with more than 2 phases, 3 more built-in options are available: "PA-PB", "PB-PA", and "|PA-PB|" refer to the (absolute value of the) difference between the means of phase means. Additionally, it is possible to specify a custom test statistic using the variable identifiers "A" and "B" (or in the case of phase deisgns with more than 2 phases, "A1", "B1", "A2", "B2", "A" and "B") and any of the basic R functions. For example, "abs(mean(A) - mean(B))" can be used as a test statistic and it will be the same as using "|A-B|".

save

Save the randomization distribution to a file (save="yes") or just see it as output in the R console (default: save="no").

limit

For phase designs: minimum number of observations per phase. For alternating treatments designs: maximum number of consecutive administrations of the same condition.

data

File in which the data can be found. Default: a window pops up in which the file can be selected.

starts

Only for multiple baseline designs: location of the file where the possible start points can be found. Default: a window pops up in which the file can be selected.

assignments

Only for user specified designs: location of the file where all the possible assignments can be found. Default: a window pops up in which the file can be selected.

Details

When using the default data argument, a window will pop up to ask in what file the data can be found. This text file containing the data should consist of two columns for single-case phase and alternation designs: the first with the condition labels and the second with the obtained scores. For multiple-baseline designs it should consist of these two columns for EACH unit. This way, each row represents one measurement occasion. It is important not to label the rows or columns.

For multiple baseline designs, when using the default starts argument, second a window pops up in which is asked in what file the possible start points can be found. In this startpoint file, each row should contain all possibilities for one unit, separated by a tab. The rows and columns should not be labeled.

For user specified designs, when using the default assignments argument, second a window pops up in which is asked in what file all the possible assignments can be found. In this file, each row should contain the sequence of conditions in one possible assignment, separated by a tab. There should be one row for every possible assignment. The rows and columns should not be labeled.

Missing data should be indicated as NA. When there is missing data, randomization distribution is generated as usual, but instead of randomly reshuffling numerical scores only, the missing data markers (NA) are also included in the reshuffling. For test statistic calculations, missing data are omitted. If test statistic cannot be calculated for a particular randomization due to insufficient data for a treatment condition, the test statistic from this randomization is conservatively considered more extreme than the observed test statistic.

When choosing to save the randomization distribution to a file, next a window will pop up (for multiple baseline designs or user specified designs this is the third pop-up window, for all other designs it is the second window) to ask where to save it. This location can be an existing file, as well as a new file that can be created by giving a file name and the extension .txt. In this latter case a confirmation is required ("The file does not exist yet. Create the file?").

References

Bulte, I., & Onghena, P. (2008). An R package for single-case randomization tests. Behavior Research Methods, 40, 467-478.

Bulte, I., & Onghena, P. (2009). Randomization tests for multiple baseline designs: An extension of the SCRT-R package. Behavior Research Methods, 41, 477-485.

Edgington, E.S., & Onghena, P. (2007). Randomization Tests (4th ed.). Boca Raton, FL: Chapman & Hall/CRC.

http://ppw.kuleuven.be/home/english/research/mesrg

See Also

distribution.systematic to generate the corresponding exhaustive randomization distribution.

observed to calculate the observed test statistic.

distribution.random to generate the nonexhaustive randomization distribution and pvalue.random to obtain the corresponding p-value.

Examples

data(ABAB)
pvalue.systematic(design = "ABAB", statistic = "PA-PB", save = "no", 
limit = 4, data = ABAB)

Number of assignment possibilities

Description

The number of assignment possibilities for the specified design is calculated.

Usage

quantity(design, MT, limit, starts = file.choose(new = FALSE), 
assignments = file.choose(new = FALSE))

Arguments

design

Type of single-case design: "AB", "ABA", "ABAB", "CRD" (completely randomized design), "RBD" (randomized block design), "ATD" (alternating treatments design), "MBD" (multiple-baseline AB design) or "Custom" (user specified design).

MT

Measurement times: number of observations.

limit

For phase designs: minimum number of observations per phase. For alternating treatments designs: maximum number of consecutive administrations of the same condition.

starts

Only for multiple baseline designs: location of the file where the possible start points can be found. Default: a window pops up in which the file can be selected.

assignments

Only for user specified designs: location of the file where all the possible assignments can be found. Default: a window pops up in which the file can be selected.

Details

For multiple baseline designs, when using the default starts argument, only the design argument is required. In this default version a window pops up in which is asked in what file the possible start points can be found. In this startpoint file, each row should contain all possibilities for one unit, separated by a tab. The rows and columns should not be labeled.

The number of possible assignments for a multiple baseline design is calculated assuming NO overlap between the possible start points of the different units (staggered administration).

For user specified designs, when using the default assignments argument, a window pops up in which is asked in what file all the possible assignments can be found. In this file, each row should contain the sequence of conditions in one possible assignment, separated by a tab. There should be one row for every possible assignment. The rows and columns should not be labeled.

References

Bulte, I., & Onghena, P. (2008). An R package for single-case randomization tests. Behavior Research Methods, 40, 467-478.

Bulte, I., & Onghena, P. (2009). Randomization tests for multiple baseline designs: An extension of the SCRT-R package. Behavior Research Methods, 41, 477-485.

http://ppw.kuleuven.be/home/english/research/mesrg

See Also

assignments to enumerate all assignment possibilities.

selectdesign to randomly select one of the assignment possibilities.

Examples

quantity(design = "ABAB", MT = 24, limit = 4)

Selection on one assignment possibility

Description

One assignment possibility is randomly selected from all theoretical possibilities.

Usage

selectdesign(design, MT, limit, starts = file.choose(new=FALSE), 
assignments = file.choose(new = FALSE))

Arguments

design

Type of single-case design: "AB", "ABA", "ABAB", "CRD" (completely randomized design), "RBD" (randomized block design), "ATD" (alternating treatments design), "MBD" (multiple-baseline AB design) or "Custom" (user specified design).

MT

Measurement times: number of observations.

limit

For phase designs: minimum number of observations per phase. For alternating treatments designs: maximum number of consecutive administrations of the same condition.

starts

Only for multiple baseline designs: location of the file where the possible start points can be found. Default: a window pops up in which the file can be selected.

assignments

Only for user specified designs: location of the file where all the possible assignments can be found. Default: a window pops up in which the file can be selected.

Details

For multiple baseline designs, when using the default starts argument, only the design argument is required. In this default version a window pops up in which is asked in what file the possible start points can be found. In this startpoint file, each row should contain all possibilities for one unit, separated by a tab. The rows and columns should not be labeled.

For user specified designs, when using the default assignments argument, first a window pops up in which is asked in what file all the possible assignments can be found. In this file, each row should contain the sequence of conditions in one possible assignment, separated by a tab. There should be one row for every possible assignment. The rows and columns should not be labeled.

For multiple baseline designs, a possible combination of start points for each unit is returned. For all other designs, a possible sequence of conditions is returned (e.g., "A" "A" "A" "A" "B" "B" "B").

References

Bulte, I., & Onghena, P. (2008). An R package for single-case randomization tests. Behavior Research Methods, 40, 467-478.

Bulte, I., & Onghena, P. (2009). Randomization tests for multiple baseline designs: An extension of the SCRT-R package. Behavior Research Methods, 41, 477-485.

http://ppw.kuleuven.be/home/english/research/mesrg

See Also

quantity to calculate the number of assignment possibilities.

assignments to enumerate all assignment possibilities.

Examples

selectdesign(design = "ABAB", MT = 24, limit = 4)