Nilosmita Banerjee

PhD studying Loss-chasing in Gambling in Big-Data @ULBruxelles @UGent |Alum @sheffieldpsy |As.Ed @efpsa_jeps | @frsFNRS FRESH Fellow

[Nilosmita Banerjee @NilosmitaB]

📢Our Systematic Scoping review with @zhangchen_psy , @LukeClark01 and #XavierNoël is now out in Neuroscience and Biobehavioural Reviews.
Check it out here ⬇️: https://t.co/R9czkxR83W
#gamblingresearch #reviews #AcademicTwitter #SCIENCE #scientists #Researchpaper
@CGR_UBC

[Current Advances in Gambling Research (CAGR) @CAGRconference]

Are you a gambling researcher based in a low- or middle-income country? Would you like to present your research at CAGR 2025, hosted by @GlaGamRes @UofGlasgow? Apply now for a full bursary! Deadline 20th Dec, 12pm GMT. Full details and link to form: https://t.co/yfTwiNKejN

[Heather Wardle @shwardle]

It was an honour to work on this, with a fantastic international team. But the hard work starts now - we need global cooperation to translate recommendations into actions

@UofGSocSci @GlaGamRes @NDARCNEWS @TheLancetPH

[The Lancet @TheLancet]

Gambling health harms are more substantial than previously understood, exacerbated by rapid global expansion & digital transformation of the industry.

A new @TheLancetPH Commission calls for regulatory reform: https://t.co/qIpQdhJA5y

[Heather Wardle @shwardle]

Spread the word @stevesharman81 @HBowdenJonesOBE @UofGSocSci @UofGSPS @GerdaReith @VirveMarionneau @Chris_Bunn @FionaDobbie @JHolmesSheff @arobertslincoln @zorroesque

[Joachim Schork @JoachimSchork]

Publication bias is a significant issue in scientific research. It occurs when studies with positive or significant results are more likely to be published than those with negative or inconclusive findings.

#DataAnalytics #VisualAnalytics #datascienceenthusiast

[Nilosmita Banerjee @NilosmitaB]

Was great presenting the poster on our latest study investigating the effects of winning and losing streaks on within-session chasing in online gambling big data at #CAGR2024 @CAGRconference

[Max Planck Society @maxplanckpress]

Good morning, everyone! Wishing you all a lovely day today ... with many inspirational squirrels!😉🐿️🐿️🐿️Cartoon by @errantscience @MCeeP

[Current Advances in Gambling Research (CAGR) @CAGRconference]

Day 1 review: we finished with the introduction of 2 new initiatives: @CharlotteEben introduced her #openscience project, and @NilosmitaB opened up registration from the new Pan European Journal Club #CAGR2024

[JEPS - Journal of European Psychology Students @efpsa_jeps]

We recruit AEs throughout the year. If you are interested, do not hesitate to contact us at [email protected] 🧡

Submissions are open anytime at https://t.co/C6IzTAXR1k!

[Nilosmita Banerjee @NilosmitaB]

Hi everyone!
We are running a survey study assessing 🎰gambling behaviour. The study takes about 15-20 mins to complete. To participate you should be 18 years old. If you are interested to participate please click the link below:
https://t.co/0KwwHngz4z

Thank you!

[Steve Sharman @stevesharman81]

Job opportunity to work with me @arobertslincoln on an @NIHRresearch funded #Gambling #research project.

https://t.co/VucNZoa17q

#postdoc #postdocposition #academia #AcademicChatter #AcademicTwitter @KingsIoPPN @Kingspsychol @PsychLincoln @KingsAddictions @SSA_Addiction

[Joël Billieux @JoelBillieux]

The landscape of open science in behavioral addiction research: Current practices and future directions

Our manuscript, led by brillant Dr @CharlotteEben ; has formally been accepted for publication!

@CarlaUnil @unil

The pre print is available here https://t.co/qFgx69e4hP

[Selçuk Korkmaz @selcukorkmaz]

🧵 Writing the Statistical Analysis Section of a Manuscript: A Guide

1/ 📜 Introduction:
When drafting a manuscript, the statistical analysis section provides clarity on how you analyzed the data. It's the backbone of your results, ensuring your findings are robust and credible.

2/ 📌 Start with Objectives:
Begin by reiterating the study's objectives or research questions. This sets the stage and reminds readers why certain analyses were performed.

3/ 📊 Descriptive Statistics:
Mention the basic descriptive statistics you utilized. This includes measures of central tendency (mean, median) and dispersion (range, standard deviation).

4/ 🔍 Specify the Tests:
Clearly state which statistical tests were used for each analysis. Whether it's t-tests, ANOVAs, regression analyses, or chi-square tests, be specific.

5/ 🛠 Software & Version:
State the statistical software package and version used. E.g., "All analyses were performed using R version 4.0.2."

6/ 🧮 Assumptions:
For many statistical tests, certain assumptions need to be met. Discuss any checks you performed (like tests for normality) and how any violations were addressed.

7/ 🔄 Handling Missing Data:
Address how you dealt with missing data – whether you used listwise deletion, imputation, or another method. Transparency is key!

8/ 🚫 Correction for Multiple Tests:
If you conducted many tests, discuss how you corrected for multiple comparisons (e.g., Bonferroni correction) to reduce the risk of Type I errors.

9/ 📈 Effect Sizes & Confidence Intervals:
Besides p-values, mention any effect sizes (like Cohen's d) and confidence intervals. They provide additional insight into the practical significance and precision of estimates.

10/ 🔄 Sensitivity Analyses:
If you conducted any sensitivity or supplementary analyses, briefly describe them. This showcases the robustness of your primary results.

11/ 🤝 Collaboration:
If you collaborated with a statistician or data analyst, mention this. It can enhance the credibility of your analysis section.

12/ 📝 Clear Language:
Use clear and concise language. Avoid jargon. The goal is to make it accessible to readers from diverse backgrounds.

13/ 🔄 Replicability:
Where possible, provide supplementary material (like a code or dataset) that would allow others to replicate your analysis.

14/ 💡 Conclusion:
Wrap up by emphasizing the rigorous approach you took. Reinforce that your methods were appropriate for answering the research questions.

15/ 🙌 Feedback:
Once your draft is ready, consider getting feedback from colleagues or a statistician. A fresh pair of eyes can spot ambiguities or errors.

📌 Final Thought:
A well-structured statistical analysis section lends credibility to your research. It ensures your study's findings are both valid and reproducible. Happy writing! 🖋

If you found this thread helpful, please like, share, and comment! #Statistics #DataScience #ResearchTips

[Nilosmita Banerjee @NilosmitaB]

In sum the reviewers said that "this paper is of exceptional value and well-timed for the field, covers an extremely central topic in problem gambling and represents a significant contribution to the literature. The authors are to be congratulated for their work on this topic."

[Nilosmita Banerjee @NilosmitaB]

📢Our Systematic Scoping review with @zhangchen_psy , @LukeClark01 and #XavierNoël is now out in Neuroscience and Biobehavioural Reviews.
Check it out here ⬇️: https://t.co/R9czkxR83W
#gamblingresearch #reviews #AcademicTwitter #SCIENCE #scientists #Researchpaper
@CGR_UBC

[Nilosmita Banerjee @NilosmitaB]

A big thanks to all my co-authors for their wonderful mentoring throughout the execution of the paper. To top it all off, we were so happy to receive some glorious comments from our reviewers on the paper.