IDEAS home Printed from https://ideas.repec.org/a/sae/miceco/v3y2015i2p77-88.html
   My bibliography  Save this article

Interlinkage between Psychological and Network Characteristics: A Preliminary Analysis

Author

Listed:
  • Abhishek Ray
  • Koushiki Sarkar
  • Diganta Mukherjee

Abstract

Humans are social beings. Every day-to-day decision as well as life-building processes are often influenced by the peer group of an individual. In this context, it may be interesting to study the actual effects of one\textquoteright s peer group on one\textquoteright s mentality. In this article, we have done a survey on an undergraduate batch of students studying in Kolkata to recognize and understand the factors that influence lifestyle, decision-making processes and major psychological characters. We observe that the social characteristics of a student significantly influence his/her psychological set-up and also vice versa. Thus, it is worth while to study a person's social surroundings and linkages to understand her psychological health.

Suggested Citation

  • Abhishek Ray & Koushiki Sarkar & Diganta Mukherjee, 2015. "Interlinkage between Psychological and Network Characteristics: A Preliminary Analysis," Studies in Microeconomics, , vol. 3(2), pages 77-88, December.
    • Handle: RePEc:sae:miceco:v:3:y:2015:i:2:p:77-88
    DOI: 10.1177/2321022215588860
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/2321022215588860
    Download Restriction: no
    File URL: https://libkey.io/10.1177/2321022215588860?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Alexander Shapiro & Jos Berge, 2002. "Statistical inference of minimum rank factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 67(1), pages 79-94, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nowak, Piotr Bolesław, 2016. "The MLE of the mean of the exponential distribution based on grouped data is stochastically increasing," Statistics & Probability Letters, Elsevier, vol. 111(C), pages 49-54.
    2. Camilo Alberto Cárdenas-Hurtado & Aaron Levi Garavito-Acosta & Jorge Hernán Toro-Córdoba, 2018. "Asymmetric Effects of Terms of Trade Shocks on Tradable and Non-tradable Investment Rates: The Colombian Case," Borradores de Economia 1043, Banco de la Republica de Colombia.
    3. Anastasiou, Andreas, 2017. "Bounds for the normal approximation of the maximum likelihood estimator from m-dependent random variables," Statistics & Probability Letters, Elsevier, vol. 129(C), pages 171-181.
    4. Evelina Di Corso & Tania Cerquitelli & Daniele Apiletti, 2018. "METATECH: METeorological Data Analysis for Thermal Energy CHaracterization by Means of Self-Learning Transparent Models," Energies, MDPI, vol. 11(6), pages 1-24, May.
    5. Silva, Ivair R., 2017. "Confidence intervals through sequential Monte Carlo," Computational Statistics & Data Analysis, Elsevier, vol. 105(C), pages 112-124.
    6. Denter, Philipp & Sisak, Dana, 2015. "Do polls create momentum in political competition?," Journal of Public Economics, Elsevier, vol. 130(C), pages 1-14.
    7. Salgado Alfredo, 2018. "Incomplete Information and Costly Signaling in College Admissions," Working Papers 2018-23, Banco de México.
    8. Albrecht, James & Anderson, Axel & Vroman, Susan, 2010. "Search by committee," Journal of Economic Theory, Elsevier, vol. 145(4), pages 1386-1407, July.
    9. Stegeman, Alwin, 2016. "A new method for simultaneous estimation of the factor model parameters, factor scores, and unique parts," Computational Statistics & Data Analysis, Elsevier, vol. 99(C), pages 189-203.
    10. Mauricio Romero & Ã lvaro Riascos & Diego Jara, 2015. "On the Optimality of Answer-Copying Indices," Journal of Educational and Behavioral Statistics, , vol. 40(5), pages 435-453, October.
    11. Chen, Yunxiao & Moustaki, Irini & Zhang, H, 2020. "A note on likelihood ratio tests for models with latent variables," LSE Research Online Documents on Economics 107490, London School of Economics and Political Science, LSE Library.
    12. Blier-Wong, Christopher & Cossette, Hélène & Marceau, Etienne, 2023. "Risk aggregation with FGM copulas," Insurance: Mathematics and Economics, Elsevier, vol. 111(C), pages 102-120.
    13. Zhu, Qiansheng & Lang, Joseph B., 2022. "Test-inversion confidence intervals for estimands in contingency tables subject to equality constraints," Computational Statistics & Data Analysis, Elsevier, vol. 169(C).
    14. van Bentum, Thomas & Cramer, Erhard, 2019. "Stochastic monotonicity of MLEs of the mean for exponentially distributed lifetimes under hybrid censoring," Statistics & Probability Letters, Elsevier, vol. 148(C), pages 1-8.
    15. Yusuke Narita, 2021. "A Theory of Quasi-Experimental Evaluation of School Quality," Management Science, INFORMS, vol. 67(8), pages 4982-5010, August.
    16. Grant J. Cameron & Hai‐Anh H. Dang & Mustafa Dinc & James Foster & Michael M. Lokshin, 2021. "Measuring the Statistical Capacity of Nations," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(4), pages 870-896, August.
    17. Simon Bruhn & Thomas Grebel & Lionel Nesta, 2023. "The fallacy in productivity decomposition," Journal of Evolutionary Economics, Springer, vol. 33(3), pages 797-835, July.
    18. Schaarschmidt, Frank & Gerhard, Daniel & Vogel, Charlotte, 2017. "Simultaneous confidence intervals for comparisons of several multinomial samples," Computational Statistics & Data Analysis, Elsevier, vol. 106(C), pages 65-76.
    19. Fernández-Duque, Mauricio, 2022. "The probability of pluralistic ignorance," Journal of Economic Theory, Elsevier, vol. 202(C).
    20. Wim J. van der Linden, 2019. "Lord’s Equity Theorem Revisited," Journal of Educational and Behavioral Statistics, , vol. 44(4), pages 415-430, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:miceco:v:3:y:2015:i:2:p:77-88. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.