University of Groningen Correlation, causation, and dynamics ......Dempster,A.P. (1972)....

21
University of Groningen Correlation, causation, and dynamics Bhushan, Nitin DOI: 10.33612/diss.126588820 IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below. Document Version Publisher's PDF, also known as Version of record Publication date: 2020 Link to publication in University of Groningen/UMCG research database Citation for published version (APA): Bhushan, N. (2020). Correlation, causation, and dynamics: Methodological innovations in sustainable energy behaviour research. [Groningen]: University of Groningen. https://doi.org/10.33612/diss.126588820 Copyright Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons). Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons the number of authors shown on this cover page is limited to 10 maximum. Download date: 23-10-2020

Transcript of University of Groningen Correlation, causation, and dynamics ......Dempster,A.P. (1972)....

Page 1: University of Groningen Correlation, causation, and dynamics ......Dempster,A.P. (1972). Covarianceselection. Biometrics,157–175. doi: 10.2307/2528966 Denholm,P.,O’Connell,M.,Brinkman,G.,&Jorgenson,J.

University of Groningen

Correlation, causation, and dynamicsBhushan, Nitin

DOI:10.33612/diss.126588820

IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite fromit. Please check the document version below.

Document VersionPublisher's PDF, also known as Version of record

Publication date:2020

Link to publication in University of Groningen/UMCG research database

Citation for published version (APA):Bhushan, N. (2020). Correlation, causation, and dynamics: Methodological innovations in sustainableenergy behaviour research. [Groningen]: University of Groningen. https://doi.org/10.33612/diss.126588820

CopyrightOther than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of theauthor(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons).

Take-down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediatelyand investigate your claim.

Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons thenumber of authors shown on this cover page is limited to 10 maximum.

Download date: 23-10-2020

Page 2: University of Groningen Correlation, causation, and dynamics ......Dempster,A.P. (1972). Covarianceselection. Biometrics,157–175. doi: 10.2307/2528966 Denholm,P.,O’Connell,M.,Brinkman,G.,&Jorgenson,J.

References

Abrahamse, W., & Steg, L. (2011). Factors related to household en-

ergy use and intention to reduce it: The role of psychological and socio-

demographic variables. Human Ecolo Review, 18(1), 30–40.

Abrahamse, W., Steg, L., Vlek, C. A., & Rothengatter, T. (2005). A review

of intervention studies aimed at household energy conservation. Journalof environmental psycholo , 25(3), 273–291. doi: 10.1016/j.jenvp.2005.08

.002

Albers, C. J. (2015). Dutch research funding, gender bias, and Simpson’s

paradox. Proceedings of the National Academy of Scienc , 112(50). doi:

10.1073/pnas.1518936112

Allcott, H., & Mullainathan, S. (2010). Behavior and energy policy. Science,327(5970), 1204–1205. doi: 10.1126/science.1180775

Azzalini, A., & Valle, A. D. (1996). The multivariate skew-normal distribu-

tion. Biometrika, 83(4), 715-726. doi: 10.1093/biomet/83.4.715

Bamberg, S., Rees, J., & Seebauer, S. (2015). Collective climate ac-

tion: Determinants of participation intention in community-based pro-

147

Page 3: University of Groningen Correlation, causation, and dynamics ......Dempster,A.P. (1972). Covarianceselection. Biometrics,157–175. doi: 10.2307/2528966 Denholm,P.,O’Connell,M.,Brinkman,G.,&Jorgenson,J.

environmental initiatives. Journal of Environmental Psycholo , 43, 155 -

165. doi: 10.1016/j.jenvp.2015.06.006

Behrens, J. T. (1997). Principles and procedures of exploratory data analy-

sis. Psychological Methods, 2(2), 131–160. doi: 10.1037/1082-989X.2.2.131

Bhushan, N., Mohnert, F., Sloot, D., Jans, L., Albers, C., & Steg, L. (2019).

Using a Gaussian graphical model to explore relationships between items

and variables in environmental psychology research. Frontiers in Psycholo ,

10, 1050. doi: 10.3389/fpsyg.2019.01050

Bhushan, N., Steg, L., & Albers, C. (2018). Studying the effects of interven-

tion programmes on household energy saving behaviours using graphical

causal models. Ener Research & Social Science, 45, 75 - 80. (Special Is-

sue on the Problems of Methods in Climate and Energy Research) doi:

10.1016/j.erss.2018.07.027

Bollen, K. A. (2002). Latent variables in psychology and the social sciences.

Annual review of psycholo , 53(1), 605–634. doi: 10.1146/annurev.psych.53.100901.135239

Borsboom, D., & Cramer, A. O. (2013). Network analysis: an integrative

approach to the structure of psychopathology. Annual review of clinicalpsycholo , 9, 91–121. doi: 10.1146/annurev-clinpsy-050212-185608

Brewer, M. B. (1991). The social self: On being the same and different at

the same time. Personality and Social Psycholo Bulletin, 17(5), 475-482.doi: 10.1177/0146167291175001

148

Page 4: University of Groningen Correlation, causation, and dynamics ......Dempster,A.P. (1972). Covarianceselection. Biometrics,157–175. doi: 10.2307/2528966 Denholm,P.,O’Connell,M.,Brinkman,G.,&Jorgenson,J.

Buurkracht. (2018). Tips om direct energiewinst halen. Retrieved from

https://buurkracht.nl/jouw-voordeel (Accessed: 21 August, 2018)

Carey, T. A., & Stiles, W. B. (2016). Some problems with randomized

controlled trials and some viable alternatives. Clinical psycholo & psy-chotherapy, 23(1), 87–95. doi: 10.1002/cpp.1942

Chatfield, C. (1985). The initial examination of data. Journal of the RoyalStatistical Society. Seri A (General), 148(3), 214–253.

Clayton, S., Devine-Wright, P., Stern, P. C., Whitmarsh, L., Carrico, A.,

Steg, L., … Bonnes, M. (2015). Psychological research and global climate

change. Nature Climate Change, 5(7), 640. doi: 10.1038/NCLIMATE2622

Cole, S. R., Platt, R. W., Schisterman, E. F., Chu, H., Westreich, D.,

Richardson, D., & Poole, C. (2010). Illustrating bias due to condition-

ing on a collider. International journal of epidemiolo , 39(2), 417–420.doi: 10.1093/ije/dyp334

Cook, T. D., Campbell, D. T., & Shadish, W. (2002). Experimental andquasi-experimental designs for generalized causal inference. Houghton

Mifflin Boston.

Cramer, A. O. J., Sluis, S., Noordhof, A., Wichers, M., Geschwind, N.,

Aggen, S. H., … Borsboom, D. (2012). Dimensions of normal person-

ality as networks in search of equilibrium: You can’t like parties if you

don’t like people. European Journal of Personality, 26 (4), 414–431. doi:

10.1002/per.1866

149

Page 5: University of Groningen Correlation, causation, and dynamics ......Dempster,A.P. (1972). Covarianceselection. Biometrics,157–175. doi: 10.2307/2528966 Denholm,P.,O’Connell,M.,Brinkman,G.,&Jorgenson,J.

Crutzen, R., & Peters, G.-J. Y. (2017). Scale quality: alpha is an inadequate

estimate and factor-analytic evidence is needed first of all. Health PsycholoReview, 11(3), 242-247. doi: 10.1080/17437199.2015.1124240

Dawid, A. P. (1980). Conditional independence for statistical operations.

The Annals of Statistics, 8(3), 598–617. doi: 10.1214/aos/1176345011

Dawid, A. P. (2010). Seeing and doing: The Pearlian synthesis. In

R. Dechter, H. Geffner, & J. Y. Halpern (Eds.),Heuristics, probability andcausality: A tribute to Judea Pearl (pp. 309–325). London: College Publi-

cations.

Deaton, A., & Cartwright, N. (2016). Understanding and misunderstand-ing randomized controlled trials (Working Paper No. 22595). National

Bureau of Economic Research. doi: http://dx.doi.org/10.3386/w22595

de Groot, J. I. M., & Steg, L. (2008). Value orientations to explain beliefs

related to environmental significant behavior: How to measure egoistic,

altruistic, and biospheric value orientations. Environment and Behavior,40(3), 330-354. doi: 10.1177/0013916506297831

de Jongh, M., & Druzdzel, M. J. (2009). A comparison of structural

distance measures for causal Bayesian network models. In M. Klopotek,

A. Przepiorkowski, S. T. Wierzchon, & K. Trojanowski (Eds.), Recent ad-vanc in intelligent information systems, challenging problems of science,computer science seri (pp. 443 – 456). Warsaw, Poland: Academic Publish-

ing House EXIT.

150

Page 6: University of Groningen Correlation, causation, and dynamics ......Dempster,A.P. (1972). Covarianceselection. Biometrics,157–175. doi: 10.2307/2528966 Denholm,P.,O’Connell,M.,Brinkman,G.,&Jorgenson,J.

Dempster, A. P. (1972). Covariance selection. Biometrics, 157–175. doi:

10.2307/2528966

Denholm, P., O’Connell, M., Brinkman, G., & Jorgenson, J. (2015). Over-generation from solar ener in California. A field guide to the duck chart(Tech. Rep.). Golden, CO (United States): National Renewable Energy

Lab.(NREL).

Dodge, Y., & Rousson, V. (2001). On asymmetric properties of the corre-

lation coefficient in the regression setting. The American Statistician, 55(1),51–54. doi: 10.1198/000313001300339932

Dong, Y., & Peng, C.-Y. J. (2013). Principled missing data methods for

researchers. SpringerPl , 2(1), 222. doi: 10.1186/2193-1801-2-222

Eberhardt, F. (2016). Introduction to the foundations of causal discovery.

International Journal of Data Science and Analytics, 3(2), 1–11. doi: 10

.1007/s41060-016-0038-6

Eftekharnejad, S., Vittal, V., Heydt, G. T., Keel, B., & Loehr, J. (2013).

Impact of increased penetration of photovoltaic generation on power

systems. IEEE Transactions on Power Systems, 28(2), 893-901. doi:

10.1109/TPWRS.2012.2216294

Elwert, F. (2013). Handbook of causal analys for social research (S. L. Mor-

gan, Ed.). Dordrecht: Springer Netherlands.

151

Page 7: University of Groningen Correlation, causation, and dynamics ......Dempster,A.P. (1972). Covarianceselection. Biometrics,157–175. doi: 10.2307/2528966 Denholm,P.,O’Connell,M.,Brinkman,G.,&Jorgenson,J.

Elwert, F., & Winship, C. (2014). Endogenous selection bias: The problem

of conditioning on a collider variable. Annual Review of Sociolo , 40, 31–53. doi: 10.1146/annurev-soc-071913-043455

Enders, C. K. (2001). A primer on maximum likelihood algorithms avail-

able for use with missing data. Structural Equation Modeling: A Multidis-ciplinary Journal, 8(1), 128-141. doi: 10.1207/S15328007SEM0801\_7

Enders, C. K., & Bandalos, D. L. (2001). The relative performance of full

information maximum likelihood estimation for missing data in structural

equation models. Structural Equation Modeling: A MultidisciplinaryJournal, 8(3), 430-457. doi: 10.1207/S15328007SEM0803\_5

Epskamp, S., Borsboom, D., & Fried, E. I. (2018). Estimating psychological

networks and their accuracy: A tutorial paper. Behavior Research Methods,50(1), 195–212. doi: 10.3758/s13428-017-0862-1

Epskamp, S., Cramer, A. O. J., Waldorp, L. J., Schmittmann, V. D., & Bors-

boom, D. (2012). qgraph: Network visualizations of relationships in psy-

chometric data. Journal of Statistical Software, 48(4), 1–18. Retrieved from

http://www.jstatsoft.org/v48/i04/ doi: 10.18637/jss.v048.i04

Fisher, R. A. (1937). The design of experiments. Oliver And Boyd; Edin-

burgh; London.

Foygel, R., & Drton, M. (2010). Extended Bayesian information criteria

for Gaussian graphical models. In Proceedings of the 23rd International

152

Page 8: University of Groningen Correlation, causation, and dynamics ......Dempster,A.P. (1972). Covarianceselection. Biometrics,157–175. doi: 10.2307/2528966 Denholm,P.,O’Connell,M.,Brinkman,G.,&Jorgenson,J.

Conference on Neural Information Processing Systems - Volume 1 (pp. 604–

612). USA: Curran Associates Inc.

Frederiks, E. R., Stenner, K., Hobman, E. V., & Fischle, M. (2016). Evalu-

ating energy behavior change programs using randomized controlled trials:

Best practice guidelines for policymakers. Ener Research & Social Science,22, 147–164. doi: 10.1016/j.erss.2016.08.020

Friedman, J., Hastie, T., & Tibshirani, R. (2008). Sparse inverse covariance

estimation with the graphical lasso. Biostatistics, 9(3), 432–441. doi: 10

.1093/biostatistics/kxm045

Friedman, J., Hastie, T., & Tibshirani, R. (2014). glasso: Graphical lasso-

estimation of Gaussian graphical models [Computer software manual].

Retrieved from https://CRAN.R-project.org/package=glasso (R

package version 1.8)

Garant, D., & Jensen, D. D. (2016). Evaluating causal models by compar-

ing interventional distributions. CoRR, abs/1608.04698 . Retrieved from

http://arxiv.org/abs/1608.04698

Gautier, A., Hoet, B., Jacqmin, J., & Van Driessche, S. (2019). Self-

consumption choice of residential pv owners under net-metering. Enerpolicy, 128 , 648–653. doi: 10.1016/j.enpol.2019.01.055

Greenland, S., Pearl, J., & Robins, J. M. (1999). Causal diagrams for

epidemiologic research. Epidemiolo , 10(1), 37–48. doi: 10.1097/

00001648-199901000-00008

153

Page 9: University of Groningen Correlation, causation, and dynamics ......Dempster,A.P. (1972). Covarianceselection. Biometrics,157–175. doi: 10.2307/2528966 Denholm,P.,O’Connell,M.,Brinkman,G.,&Jorgenson,J.

Haavelmo, T. (1943). The statistical implications of a system of simultane-

ous equations. Econometrica, 11(1), 1–12. doi: 10.2307/1905714

Hastie, T., & Tibshirani, R. (1986). Generalized additive models. StatisticalScience, 1(3), 297–310. doi: 10.1214/ss/1177013604

Heckman, J. J. (2006). Rejoinder: Response to Sobel. Sociological Method-olo , 35(1), 135-150. doi: 10.1111/j.0081-1750.2006.00166.x

Heinze-Deml, C., Maathuis, M. H., & Meinshausen, N. (2018). Causal

structure learning. Annual Review of Statistics and Its Application, 5(1),371-391. doi: 10.1146/annurev-statistics-031017-100630

Hernán, M. A., & Taubman, S. L. (2008). Does obesity shorten life? The

importance of well-defined interventions to answer causal questions. Inter-national journal of obesity, 32, 8–14. doi: 10.1038/ijo.2008.82

Hornsey, M. J., & Jetten, J. (2004). The individual within the group:

Balancing the need to belong with the need to be different. Personality andSocial Psycholo Review, 8(3), 248–264. doi: 10.1207/s15327957pspr0803\

_2

Hyvärinen, A., & Smith, S. M. (2013). Pairwise likelihood ratios for esti-

mation of non-Gaussian structural equation models. Journal of MachineLearning Research, 14(1), 111–152.

IPCC. (2014). Climate Change 2014–Impacts, Adaptation and Vulnera-bility: Regional Aspects. Cambridge, United Kingdom and New York, NY,

USA: Cambridge University Press.

154

Page 10: University of Groningen Correlation, causation, and dynamics ......Dempster,A.P. (1972). Covarianceselection. Biometrics,157–175. doi: 10.2307/2528966 Denholm,P.,O’Connell,M.,Brinkman,G.,&Jorgenson,J.

Jans, L., Postmes, T., & Van der Zee, K. I. (2011). The induction of

shared identity: The positive role of individual distinctiveness for groups.

Personality and Social Psycholo Bulletin, 37(8), 1130–1141. doi:

10.1177/0146167211407342

Jones, P. J., Mair, P., & McNally, R. J. (2018). Visualizing psychological

networks: A tutorial in R. Frontiers in Psycholo , 9, 1742. doi: 10.3389/

fpsyg.2018.01742

Kalisch, M., & Bühlmann, P. (2007). Estimating high-dimensional di-

rected acyclic graphs with the PC-algorithm. Journal of Machine LearningResearch, 8(1), 613–636.

Kalisch, M., Mächler, M., Colombo, D., Maathuis, M. H., & Bühlmann, P.

(2012). Causal inference using graphical models with the R package pcalg.

Journal of Statistical Software, 47(11), 1–26. doi: 10.18637/jss.v047.i11

Karlin, B., Zinger, J. F., & Ford, R. (2015). The effects of feedback on

energy conservation: A meta-analysis. Psychological Bulletin, 141(6), 1205-1227. doi: 10.1037/a0039650

Keirstead, J. (2007). Behavioural responses to photovoltaic systems in

the UK domestic sector. Ener Policy, 35(8), 4128–4141. doi: 10.1016/

j.enpol.2007.02.019

Kievit, R. A., Frankenhuis, W. E., Waldorp, L. J., & Borsboom, D. (2013).

Simpson’s paradox in psychological science: a practical guide. Frontiers inPsycholo , 4, 513. doi: 10.3389/fpsyg.2013.00513

155

Page 11: University of Groningen Correlation, causation, and dynamics ......Dempster,A.P. (1972). Covarianceselection. Biometrics,157–175. doi: 10.2307/2528966 Denholm,P.,O’Connell,M.,Brinkman,G.,&Jorgenson,J.

Klaassen, E., Frunt, J., & Slootweg, J. (2015). Assessing the impact of

distributed energy resources on LV grids using practical measurements. In

23rd Interanational Conference on Electricity Distribution (CIRED), 15-18June 2015, Lyon, France (pp. 1289–1).

Kobus, C. B., Mugge, R., & Schoormans, J. P. (2013). Washing when the

sun is shining! How users interact with a household energy management

system. Ergonomics, 56 (3), 451-462. doi: 10.1080/00140139.2012.721522

Koller, D., & Friedman, N. (2009). Probabilistic graphical models: Prin-cipl and techniqu - Adaptive computation and machine learning. Cam-

bridge, Massachusetts: The MIT Press.

Lauritzen, S. (2001). Causal inference from graphical models. In

O. E. Barndorff-Nielsen, D. R. Cox, & C. Klüppelberg (Eds.), Complexstochastic systems (pp. 63–107). London/Boca Raton: Chapman and Hal-

l/CRC Press.

Lauritzen, S. L. (1996). Graphical models (Vol. 17). Oxford: Clarendon

Press.

Leach, C. W., Van Zomeren, M., Zebel, S., Vliek, M. L., Pennekamp, S. F.,

Doosje, B., … Spears, R. (2008). Group-level self-definition and self-

investment: a hierarchical (multicomponent) model of in-group identifi-

cation. Journal of Personality and Social Psycholo , 95(1), 144–165. doi:

10.1037/0022-3514.95.1.144

156

Page 12: University of Groningen Correlation, causation, and dynamics ......Dempster,A.P. (1972). Covarianceselection. Biometrics,157–175. doi: 10.2307/2528966 Denholm,P.,O’Connell,M.,Brinkman,G.,&Jorgenson,J.

Lilienfeld, S. O., McKay, D., & Hollon, S. D. (2018). Why randomised

controlled trials of psychological treatments are still essential. The LancetPsychiatry, 5(7), 536–538. doi: 10.1016/S2215-0366(18)30045-2

Luthander, R., Widén, J., Nilsson, D., & Palm, J. (2015). Photovoltaic

self-consumption in buildings: A review. Applied ener , 142, 80–94. doi:

10.1016/j.apenergy.2014.12.028

Lynn, M., & Snyder, C. R. (2002). Uniqueness seeking. In C. R. Snyder

& S. J. Lopez (Eds.),Handbook of positive psycholo (pp. 395–410). New

York, NY, US: Oxford University Press.

Masson, T., Jugert, P., & Fritsche, I. (2016). Collective self-fulfilling

prophecies: group identification biases perceptions of environmental group

norms among high identifiers. Social Influence, 11(3), 185-198. doi:

10.1080/15534510.2016.1216890

Meehl, P. E. (1990). Why summaries of research on psychological theories

are often uninterpretable. Psychological reports, 66 (1), 195–244. doi: 10

.2466/PR0.66.1.195-244

Meinshausen, N., & Bühlmann, P. (2010). Stability selection. Journal ofthe Royal Statistical Society: Seri B (statistical methodolo ), 72(4), 417-473. doi: 10.1111/j.1467-9868.2010.00740.x

Nicholls, L., & Strengers, Y. (2015). Peak demand and the ‘family peak’

period in Australia: Understanding practice (in) flexibility in households

157

Page 13: University of Groningen Correlation, causation, and dynamics ......Dempster,A.P. (1972). Covarianceselection. Biometrics,157–175. doi: 10.2307/2528966 Denholm,P.,O’Connell,M.,Brinkman,G.,&Jorgenson,J.

with children. Ener Research & Social Science, 9, 116–124. doi: 10.1016/

j.erss.2015.08.018

Nichols, A. L., & Webster, G. D. (2013). The single-item need to belong

scale. Personality and Individual Differenc , 55(2), 189 - 192. doi: 10.1016/

j.paid.2013.02.018

Norwegian Centre for Research Data. (2016a). European social surveyround 8 data file edition 2.1. Data Archive and distributor of ESS data for

ESS ERIC.

Norwegian Centre for Research Data. (2016b). European social surveyround 8 module on public attitud to climate change. Data Archive and

distributor of ESS data for ESS ERIC.

Oberst, C. A., Schmitz, H., & Madlener, R. (2019). Are prosumer

households that much different? Evidence from stated residential energy

consumption in Germany. Ecological Economics, 158 , 101–115. doi:

10.1016/j.ecolecon.2018.12.014

Pearl, J. (2009). Causality: Models, reasoning and inference (2nd ed.). New

York, NY, USA: Cambridge University Press.

Pearl, J. (2014). Comment: Understanding Simpson’s paradox. TheAmerican Statistician, 68(1), 8-13. doi: 10.1080/00031305.2014.876829

Peters, A. M., van der Werff, E., & Steg, L. (2019). Mind the gap: The

implications of not acting in line with your planned actions after installing

158

Page 14: University of Groningen Correlation, causation, and dynamics ......Dempster,A.P. (1972). Covarianceselection. Biometrics,157–175. doi: 10.2307/2528966 Denholm,P.,O’Connell,M.,Brinkman,G.,&Jorgenson,J.

solar photovoltaics. Frontiers in Psycholo , 10, 1423. doi: 10.3389/fpsyg

.2019.01423

Peters, J. (2015). Sid: Structural intervention distance [Computer software

manual]. Retrieved from https://CRAN.R-project.org/package=SID

(R package version 1.0)

Peters, J., & Bühlmann, P. (2015). Structural intervention distance for

evaluating causal graphs. Neural Computation, 27(3), 771–799. doi: 10

.1162/NECO\_a\_00708

Postmes, T., Baray, G., Haslam, S. A., Morton, T. A., & Swaab, R. I.

(2006). The dynamics of personal and social identity formation. In

T. Postmes & J. Jetten (Eds.), Individuality and the group : Advanc insocial identity (p. 215-236). Thousand Oaks, CA, US: Sage Publications,

Inc. doi: 10.4135/9781446211946.n12

Postmes, T., Haslam, S. A., & Jans, L. (2013). A single-item measure of

social identification: reliability, validity, and utility. British journal of socialpsycholo , 52(4), 597–617. doi: 10.1111/bjso.12006

Postmes, T., Haslam, S. A., & Swaab, R. I. (2005). Social influence in small

groups: An interactive model of social identity formation. European reviewof social psycholo , 16 (01), 1–42. doi: 10.1080/10463280440000062

R Core Team. (2017). R: A Language and Environment for StatisticalComputing. Vienna, Austria. Retrieved from https://www.R-project

.org/

159

Page 15: University of Groningen Correlation, causation, and dynamics ......Dempster,A.P. (1972). Covarianceselection. Biometrics,157–175. doi: 10.2307/2528966 Denholm,P.,O’Connell,M.,Brinkman,G.,&Jorgenson,J.

Revelle, W. (2018). psych: Procedures for psychological, psychometric,

and personality research [Computer software manual]. Evanston, Illinois.

Retrieved from https://CRAN.R-project.org/package=psych (R

package version 1.8.12)

RStudio Team. (2017). RStudio: Integrated Development Environment

for R [Computer software manual]. Boston, MA. Retrieved from http://

www.rstudio.com/

Rücker, G., & Schwarzer, G. (2014, 12). Presenting simulation results in

a nested loop plot. BMCMedical Research Methodolo , 14(1), 129. doi:

10.1186/1471-2288-14-129

Schafer, J. L. (1997). Analys of incomplete multivariate data. London:

Chapman and Hall/CRC.

Schafer, J. L., & Graham, J. W. (2002). Missing data: our view of the state

of the art. Psychological methods, 7(2), 147. doi: 10.1037/1082-989X.7.2.147

Schick, L., & Gad, C. (2015). Flexible and inflexible energy engagements—

A study of the Danish smart grid strategy. Ener Research & Social Sci-ence, 9, 51–59. doi: 10.1016/j.erss.2015.08.013

Schill, W.-P., Zerrahn, A., & Kunz, F. (2017). Prosumage of solar electric-

ity: pros, cons, and the system perspective. DIW Berlin Discussion PaperNo. 1637 . doi: 10.2139/ssrn.2912814

Schmitt, N. (1996). Uses and abuses of coefficient alpha. Psychologicalassessment, 8(4), 350. doi: 10.1037/1040-3590.8.4.350

160

Page 16: University of Groningen Correlation, causation, and dynamics ......Dempster,A.P. (1972). Covarianceselection. Biometrics,157–175. doi: 10.2307/2528966 Denholm,P.,O’Connell,M.,Brinkman,G.,&Jorgenson,J.

Shadish, W. R., Clark, M. H., & Steiner, P. M. (2008). Can nonrandomized

experiments yield accurate answers? A randomized experiment comparing

random and nonrandom assignments. Journal of the American StatisticalAssociation, 103(484), 1334-1344. doi: 10.1198/016214508000000733

Shimizu, S., Hoyer, P. O., Hyvarinen, A., & Kerminen, A. (2006). A

linear non-Gaussian acyclic model for causal discovery. Journal of MachineLearning Research, 7 , 2003–2030.

Shimizu, S., Inazumi, T., Sogawa, Y., Hyvärinen, A., Kawahara, Y., Washio,

T., … Bollen, K. (2011). Directlingam: A direct method for learning a linear

non-Gaussian structural equation model. Journal of Machine LearningResearch, 12(2), 1225–1248.

Shrier, I., & Platt, R. W. (2008). Reducing bias through directed acyclic

graphs. BMC medical research methodolo , 8(1), 70. doi: 10.1186/1471

-2288-8-70

Sloot, D., Jans, L., & Steg, L. (2017). The potential of environmental com-

munity initiatives - a social psychological perspective. In A. K. Römpke,

G. Reese, I. Fritsche, N. Wiersbinski, & A. W. Mues (Eds.),Outlooks onapplying environmental psycholo research (pp. 27–34). Bonn: Federal

Agency for Nature Conservation. doi: 10.19217/skr460

Sloot, D., Jans, L., & Steg, L. (2018). Can community energy initiatives

motivate sustainable energy behaviours? The role of initiative involvement

161

Page 17: University of Groningen Correlation, causation, and dynamics ......Dempster,A.P. (1972). Covarianceselection. Biometrics,157–175. doi: 10.2307/2528966 Denholm,P.,O’Connell,M.,Brinkman,G.,&Jorgenson,J.

and personal pro-environmental motivation. Journal of EnvironmentalPsycholo , 57 , 99 - 106. doi: 10.1016/j.jenvp.2018.06.007

Sommerfeld, J., Buys, L., & Vine, D. (2017). Residential consumers’ expe-

riences in the adoption and use of solar PV. Ener Policy, 105, 10-16. doi:

10.1016/j.enpol.2017.02.021

Sóskuthy, M. (2017). Generalised additive mixed models for dynamic

analysis in linguistics: a practical introduction. arXiv e-prints.

Sovacool, B. K. (2014). What are we doing here? Analyzing fifteen years of

energy scholarship and proposing a social science research agenda. EnerResearch & Social Science, 1, 1 - 29. doi: 10.1016/j.erss.2014.02.003

Spirtes, P., Glymour, C. N., & Scheines, R. (2000). Causation, prediction,and search. Cambridge, MA, USA: MIT press.

Spirtes, P., Meek, C., & Richardson, T. (1995). Causal inference in the

presence of latent variables and selection bias. In P. Besnard & S. Hanks

(Eds.), Proceedings of the Eleventh Conference on Uncertainty in ArtificialIntelligence (pp. 499–506). San Francisco, CA, USA: Morgan Kaufmann

Publishers Inc.

Spirtes, P., & Zhang, K. (2016). Causal discovery and inference: concepts

and recent methodological advances. Applied Informatics, 3(1), 3. doi:

10.1186/s40535-016-0018-x

162

Page 18: University of Groningen Correlation, causation, and dynamics ......Dempster,A.P. (1972). Covarianceselection. Biometrics,157–175. doi: 10.2307/2528966 Denholm,P.,O’Connell,M.,Brinkman,G.,&Jorgenson,J.

Steg, L., Dreijerink, L., & Abrahamse, W. (2005). Factors influencing the

acceptability of energy policies: A test of VBN theory. Journal of Environ-mental Psycholo , 25(4), 415–425. doi: 10.1016/j.jenvp.2005.08.003

Steg, L., Perlaviciute, G., & van der Werff, E. (2015). Understanding the

human dimensions of a sustainable energy transition. Frontiers in Psychol-o , 6 , 805. doi: 10.3389/fpsyg.2015.00805

Steg, L., Perlaviciute, G., van der Werff, E., & Lurvink, J. (2014). The

significance of hedonic values for environmentally relevant attitudes, pref-

erences, and actions. Environment and Behavior, 46 (2), 163-192. doi:

10.1177/0013916512454730

Steiner, P. M., Kim, Y., Hall, C. E., & Su, D. (2017). Graphical models

for quasi-experimental designs. Sociological Methods & Research, 46 (2),155-188. doi: 10.1177/0049124115582272

Stern, P. C. (2000). New environmental theories: toward a coherent theory

of environmentally significant behavior. Journal of Social Issu , 56 (3),407–424. doi: 10.1111/0022-4537.00175

Tajfel, H., & Turner, J. C. (2001). An integrative theory of intergroup con-

flict. In M. A. Hogg & D. Abrams (Eds.),Key readings in social psycholo .intergroup relations: Essential readings (p. 94-109). New York, NY, US:

Psychology Press.

Textor, J., van der Zander, B., Gilthorpe, M. S., Liśkiewicz, M., & Ellison,

G. T. (2016). Robust causal inference using directed acyclic graphs: the R

163

Page 19: University of Groningen Correlation, causation, and dynamics ......Dempster,A.P. (1972). Covarianceselection. Biometrics,157–175. doi: 10.2307/2528966 Denholm,P.,O’Connell,M.,Brinkman,G.,&Jorgenson,J.

package “dagitty”. International journal of epidemiolo , 45(6), 1887–1894.doi: 10.1093/ije/dyw341

Tiefenbeck, V., Staake, T., Roth, K., & Sachs, O. (2013). For better or

for worse? Empirical evidence of moral licensing in a behavioral energy

conservation campaign. Ener Policy, 57 , 160–171. doi: 10.1016/j.enpol

.2013.01.021

Tukey, J. W. (1977). Exploratory data analys (Vol. 2). Reading, Mass.:

Addison-Wesley.

Turner, J. C. (1991). Mapping social psycholo seri . social influence.Belmont, CA, US: Thomson Brooks/Cole Publishing Co.

van Rij, J., Wieling, M., Baayen, R. H., & van Rijn, H. (2017). itsadug:Interpreting time seri and autocorrelated data using GAMMs. (R package

version 2.3)

van Borkulo, C., Boschloo, L., Kossakowski, J., Tio, P., Schoevers, R., Bors-

boom, D., & Boschloo, L. (2017). Comparing network structur on threeaspects. Working Paper. doi: 10.13140/RG.2.2.29455.38569

Vandenbroucke, J. P. (2008, 03). Observational research, randomised

trials, and two views of medical science. PLOS Medicine, 5(3), 1-5. doi:

10.1371/journal.pmed.0050067

Van der Werff, E., Steg, L., & Keizer, K. (2013). The value of envi-

ronmental self-identity: The relationship between biospheric values,

164

Page 20: University of Groningen Correlation, causation, and dynamics ......Dempster,A.P. (1972). Covarianceselection. Biometrics,157–175. doi: 10.2307/2528966 Denholm,P.,O’Connell,M.,Brinkman,G.,&Jorgenson,J.

environmental self-identity and environmental preferences, intentions

and behaviour. Journal of Environmental Psycholo , 34, 55–63. doi:

10.1016/j.jenvp.2012.12.006

Van Zomeren, M., Spears, R., Fischer, A. H., & Leach, C. W. (2004). Put

your money where your mouth is! Explaining collective action tendencies

through group-based anger and group efficacy. Journal of Personality andSocial Psycholo , 87(5), 649–664. doi: 10.1037/0022-3514.87.5.649

Vine, E., Sullivan, M., Lutzenhiser, L., Blumstein, C., & Miller, B. (2014).

Experimentation and the evaluation of energy efficiency programs. EnerEfficiency, 7(4), 627–640. doi: 10.1007/s12053-013-9244-4

West, S. G. (2009). Alternatives to randomized experiments. CurrentDirections in Psychological Science, 18(5), 299-304. doi: 10.1111/j.1467-8721

.2009.01656.x

Whittaker, J. (2009). Graphical models in applied multivariate statistics.Chichester, England: Wiley Publishing.

Wieling, M. (2018). Analyzing dynamic phonetic data using generalized

additive mixed modeling: a tutorial focusing on articulatory differences

between L1 and L2 speakers of English. Journal of Phonetics, 70, 86–116.doi: 10.1016/j.wocn.2018.03.002

Wittenberg, I., & Matthies, E. (2016). Solar policy and practice in germany:

How do residential households with solar panels use electricity? EnerResearch & Social Science, 21, 199–211. doi: 10.1016/j.erss.2016.07.008

165

Page 21: University of Groningen Correlation, causation, and dynamics ......Dempster,A.P. (1972). Covarianceselection. Biometrics,157–175. doi: 10.2307/2528966 Denholm,P.,O’Connell,M.,Brinkman,G.,&Jorgenson,J.

Wood, S. (2017). Generalized Additive Models: An Introduction with R,Second Edition. Boca Raton, Florida, USA: Chapman & Hall/CRC Press.

doi: 10.1201/9781315370279

Wood, S., Pya, N., & Säfken, B. (2016). Smoothing parameter and model

selection for general smooth models. Journal of the American StatisticalAssociation, 111(516), 1548–1563. doi: 10.1080/01621459.2016.1180986

Wright, S. (1934). The method of path coefficients. The Annals of Mathe-matical Statistics, 5(3), 161–215. doi: 10.1214/aoms/1177732676

Zhang, J. (2008, 11). On the completeness of orientation rules for causal

discovery in the presence of latent confounders and selection bias. ArtificialIntelligence, 172(16-17), 1873–1896. doi: 10.1016/j.artint.2008.08.001

166