An R package containing commonly used functions for analyzing behavioral economic demand curve data.
Install and load the devtools package. Then, use install_github to install the package and associated vignette.
install.packages("devtools")
install.packages("digest")
devtools::install_github("brentkaplan/beezdemand", build_vignettes = TRUE)
library(beezdemand)Currently, this version (0.0.95) is under development. You are free to use it, but be aware that there might be bugs present. If you find issues or would like to contribute, please contact me at bkaplan.ku@gmail.com.
Example dataset of responses on an Alcohol Purchase Task. Participants (id) reported the number of alcoholic drinks (y) they would be willing to purchase and consume at various prices (x; USD). Note the long format.
>apt[c(1:8, 17:24), ]
id x y
1 19 0.0 10
2 19 0.5 10
3 19 1.0 10
4 19 1.5 8
5 19 2.0 8
6 19 2.5 8
7 19 3.0 7
8 19 4.0 7
17 30 0.0 3
18 30 0.5 3
19 30 1.0 3
20 30 1.5 3
21 30 2.0 2
22 30 2.5 2
23 30 3.0 2
24 30 4.0 2Descriptive values of responses at each price. Includes mean, standard deviation, proportion of zeros, and numer of NAs.
> GetDescriptives(apt)
0 0.5 1 1.5 2 2.5 3 4 5 6 7 8 9 10
Mean 6.80 6.80 6.50 6.10 5.30 5.20 4.80 4.30 3.90 3.50 3.30 2.60 2.40 2.20
SD 2.62 2.62 2.27 1.91 1.89 1.87 1.48 1.57 1.45 1.43 1.34 1.51 1.58 1.32
PropZeros 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.10 0.10
NAs 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
15 20
Mean 1.10 0.80
SD 1.37 1.14
PropZeros 0.50 0.60
NAs 0.00 0.00Examine consistency of demand data using Stein et al.’s (2015) alogrithm for identifying unsystematic responses. Default values shown.
> head(CheckUnsystematic(apt, deltaq = 0.025, bounce = 0.1, reversals = 0, ncons0 = 2), 3)
Participant TotalPass DeltaQ DeltaQPass Bounce BouncePass Reversals
1 19 3 0.2112 Pass 0 Pass 0
2 30 3 0.1437 Pass 0 Pass 0
3 38 3 0.7885 Pass 0 Pass 0
ReversalsPass NumPosValues
1 Pass 16
2 Pass 16
3 Pass 14Results of the analysis return both empirical and derived measures for use in additional analyses and model specification.
> head(FitCurves(apt, "hs"), 3)
Participant Q0e BP0 BP1 Omaxe Pmaxe Equation Q0 K R2
1 19 10 NA 20 45 15 hs 10.492736 1 0.9643380
2 30 3 NA 20 20 20 hs 2.942614 1 0.7934822
3 38 4 15 10 21 7 hs 4.525925 1 0.8656883
Alpha Q0se Alphase N AbsSS SdRes Q0Low
1 0.004856258 0.4312016 0.0002574193 16 0.02028108 0.03806112 9.567901
2 0.014057972 0.2531714 0.0018292289 16 0.09724906 0.08334484 2.399616
3 0.009120746 0.2373820 0.0009315781 14 0.02601971 0.04656511 4.008714
Q0High AlphaLow AlphaHigh EV Omaxd Pmaxd Notes
1 11.417572 0.004304148 0.005408367 2.0591989 45.63181 14.38512 converged
2 3.485613 0.010134666 0.017981278 0.7113402 15.76329 17.71936 converged
3 5.043136 0.007091012 0.011150481 1.0964015 24.29624 17.75686 converged
> head(FitCurves(apt, "koff"), 3)
Participant Q0e BP0 BP1 Omaxe Pmaxe Equation Q0 K R2
1 19 10 NA 20 45 15 koff 10.219980 1 0.9636911
2 30 3 NA 20 20 20 koff 3.025350 1 0.8188253
3 38 4 15 10 21 7 koff 4.599041 1 0.8182557
Alpha Q0se Alphase N AbsSS SdRes Q0Low Q0High
1 0.004501826 0.2673350 0.0002894209 16 3.186106 0.4770524 9.646603 10.793356
2 0.014498545 0.1780691 0.0021436221 16 1.449398 0.3217583 2.643430 3.407271
3 0.010588272 0.3414723 0.0018843340 16 5.043406 0.6002027 3.866656 5.331426
AlphaLow AlphaHigh EV Omaxd Pmaxd Notes
1 0.003881080 0.005122573 2.2213207 49.22443 15.93181 converged
2 0.009900933 0.019096158 0.6897244 15.28428 16.71106 converged
3 0.006546778 0.014629766 0.9444412 20.92880 15.05260 convergedProvides the ability to share k globally (across all participants) while estimating Q0 and alpha locally.
> head(FitCurves(apt, "hs", k = "share"), 3)
Participant Q0e BP0 BP1 Omaxe Pmaxe Equation Q0d SharedK R2
1 19 10 NA 20 45 15 hs 10.0146 3.3183 0.98210
2 30 3 NA 20 20 20 hs 2.7663 3.3183 0.76418
3 38 4 15 10 21 7 hs 4.4858 3.3183 0.88031
Alpha Q0se Alphase N AbsSS SdRes Q0Low Q0High AlphaLow
1 0.0011616 0.24291 3.0813e-05 16 0.010182 0.026968 9.4936 10.5356 0.0010955
2 0.0033331 0.21928 3.7389e-04 16 0.111049 0.089062 2.2960 3.2366 0.0025312
3 0.0024580 0.20750 1.9633e-04 14 0.023186 0.043957 4.0337 4.9379 0.0020302
AlphaHigh EVd Omaxd Pmaxd Notes
1 0.0012277 1.42418 44.552 13.161 converged
2 0.0041350 0.49633 15.526 16.604 converged
3 0.0028858 0.67304 21.054 13.885 convergedTo learn more about a function and what arguments it takes, type “?” in front of the function name.
> ?CheckUnsystematic
CheckUnsystematic package:beezdemand R Documentation
Systematic Purchase Task Data Checker
Description:
Applies Stein, Koffarnus, Snider, Quisenberry, & Bickel's (2015)
criteria for identification of nonsystematic purchase task data.
...Derek D. Reed, Applied Behavioral Economics Laboratory (www.behavioraleconlab.com)
Paul E. Johnson, Center for Research Methods and Data Analysis, University of Kansas (www.crmda.ku.edu)
Michael Amlung, Cognitive Neuroscience of Addictions Laboratory (www.cnalab.weebly.com)
Peter G. Roma, Institutes for Behavior Resources, Inc. (www.ibrinc.org)
Steven R. Hursh, Institutes for Behavior Resources, Inc. (www.ibrinc.org)
Shawn P. Gilroy, GitHub
Reed, D. D., Niileksela, C. R., & Kaplan, B. A. (2013). Behavioral economics: A tutorial for behavior analysts in practice. Behavior Analysis in Practice, 6 (1), 34–54.
Reed, D. D., Kaplan, B. A., & Becirevic, A. (2015). Basic research on the behavioral economics of reinforcer value. In Autism Service Delivery (pp. 279-306). Springer New York.
Hursh, S. R., & Silberberg, A. (2008). Economic demand and essential value. Psychological Review, 115 (1), 186-198.
Koffarnus, M. N., Franck, C. T., Stein, J. S., & Bickel, W. K. (2015). A modified exponential behavioral economic demand model to better describe consumption data. Experimental and Clinical Psychopharmacology, 23 (6), 504-512.
Stein, J. S., Koffarnus, M. N., Snider, S. E., Quisenberry, A. J., & Bickel, W. K. (2015). Identification and management of nonsystematic purchase task data: Toward best practice. Experimental and Clinical Psychopharmacology
Have a question? Have a suggestion for a feature? Would you like to contribute? Email me at bkaplan.ku@gmail.com.
GPL Version 2 or later