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How Temporary Are Temporary Student Visas? @nicokreis, J. Van Hook, and H. Persaud use #longitudinaldata to study the factors influencing the potential transition to #permanentresidence for #internationalstudents. Read: doi.org/10.1177/237802312514…
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30 Sep 2025
New TILDA publication! The Cohort Profile Update on TILDA (Waves 5 & 6) is now out in the @IntJEpidemiol Read the full paper here: bit.ly/48D6hLV #AgeingResearch #Epidemiology #LongitudinalData @SiobhanScar @RoseAnnekenny1 @CathalMcCrory1 @tcddublin @TrinityMed1
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🔔 Editorial Update | Clinical and Experimental Obstetrics & Gynecology 🎉 We are delighted to welcome Dr. Hassan Jafari to the Editorial Board as Statistics Editor! 👤 Profile of Dr. Hassan Jafari Dr. Hassan Jafari is a Clinical Trial Statistician in the Department of Biostatistics and Health Informatics at King's College London(@KingsCollegeLon ), working primarily on the setup, conduct, and analysis of clinical trials supported by the King’s Clinical Trials Unit. He is proficient in statistical software including #R, #STATA, #Python, #SPSS, and #JMP, with expertise in data management, advanced modelling, and visualization. 🏪 Affiliation: King's College London(@KingsCollegeLon ) · Department of Biostatistics and Health Informatics King’s Clinical Trial Unit, London, UK Interests: Biostatistics, Clinical trial methodology, Time-to-Event analysis, Longitudinal data analysis, Linear Mixed Models, Meta Analysis, Psychometrics 🔗 Website:imrpress.com/journal/CEOG/ab… We are pleased to welcome Dr. Hassan Jafari to the Editorial Board and look forward to working together towards the continued progress of the Clinical and Experimental Obstetrics & Gynecology. #EditorialBoard #Biostatistics #ClinicalTrials #ClinicalResearch #StatisticsEditor #TimeToEventAnalysis #LongitudinalData #MetaAnalysis #CEOG #MedicalResearch
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Need GPC data for your next project? GPC data is accessible to bona fide researchers. We make it easy: 📍Review available datasets 📍Submit a short concept note 📍Connect with our data access committee Get started here: lshtm.ac.uk/research/centres… #OpenScience #AfricaDataHub #PopulationHealth #MRCUganda #LongitudinalData
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From HIV to non-communicable diseases, ageing, and social determinants of health, work at the GPC isn’t static. With robust data spanning health, behaviour, and environment, our work informs both science and policy. Curious about what we’re exploring now? Dive in: lshtm.ac.uk/research/centres… #PopulationHealth #MRCUganda #LongitudinalData
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Ever heard of the General Population Cohort (GPC)? Based in rural southwestern Uganda, the GPC is one of Africa’s richest long-term population health resources, tracking data for over 35 years. More than just another dataset, it’s a window into how health, society, and systems evolve and adapt over time. Learn more: lshtm.ac.uk/research/centres… #PopulationHealth #MRCUganda #LongitudinalData
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📢 New data released! The complete third #FReDA wave is now freely available via @gesis_org – perfect for longitudinal studies. 👉 Get access: search.gesis.org/research_da… #SocialScience #PanelData #LongitudinalData
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13 May 2025
This week on the #LinkingOurLivesPod we explore the power of the @ONS LS & its Scottish counterpart (@SLS_DSU) with geographers @pdqnorman & Tom Clemens! 🔗 shorturl.at/bxFNq #LongitudinalData #Geography @GeosciencesEd @ESRC @UKRI_News @researchpods @EdinburghUni
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12 Mar 2025
Introducing TIMER⌛️: a temporal instruction modeling and evaluation framework for longitudinal clinical records! 🏥📈 TIMER tackles challenges in processing longitudinal medical records—including temporal reasoning, multi-visit synthesis, and patient trajectory analysis. It introduces: 🔹 Time-aware benchmarks to evaluate temporal reasoning abilities 🔹 Temporal instruction tuning for enhanced longitudinal understanding 🔹 Distribution-aware training strategies for balanced temporal coverage Featured Highlights 💡 🔍 TIMER-Bench: First benchmark specifically designed to evaluate temporal reasoning across longitudinal EHRs with explicit datetime grounding for each instruction-response pair 🧩 TIMER-Instruct: Temporal instruction tuning methodology that improves models' ability to reason across patient timelines ⏱️ Multi-timepoint reasoning capabilities—enabling synthesis across different parts of long contexts in the patient records 📋 The "lost-in-the-middle" phenomenon of model-generated instruction response pairs given long-context input—models naturally focus on timeline edges while overlooking critical middle periods 🔬 Three temporal distribution strategies for comprehensive evaluation: recency-focused, edge-focused, and uniformly distributed 📊 Performance: TIMER achieves improvements on clinical benchmarks: 📈 7.3% improvement on physician-generated MedAlign benchmark 📈 9.2% improvement on temporal reasoning on TIMER-Bench 📊 Robust performance with uniformly distributed instruction tuning 🌟 Why TIMER matters: 1️⃣ Physicians routinely analyze EHRs spanning years and thousands of entries 2️⃣ Clinical decisions require understanding complex relationships across time periods 3️⃣ Existing medical LLM benchmarks focus on static QAs, leading to longitudinal evaluation gaps 4️⃣ TIMER bridges these gaps with temporal reasoning capabilities 📄 Read our paper: arxiv.org/abs/2503.04176 👥 Huge thanks to my many collaborators on this project, including @AlyssaUnell, @chenbowen118, @jasonafries, @Emily_Alsentzer, @sanmikoyejo, @drnigam, as well as feedback from the teams at @stai_research and the Shah Lab. #LLMs #TemporalReasoning #LongitudinalData #HealthcareAI

1/🧵Introducing TIMER: Temporal Instruction Modeling and Evaluation for Longitudinal Clinical Records When we evaluate LLMs for reasoning over longitudinal clinical records, can we leverage synthetic data generation to create scalable benchmarks and improve model performance?
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Participants on @OfficialUoM's Introduction to Longitudinal Data Analysis course will learn how to clean and analyse #LongitudinalData. Dr Alexandru Cernat (@cernat_a ) of @SocialStatsMan will lead the five-day course (13 March-11 April). Register: ncrm.ac.uk/training/show.php…
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Mixed models are crucial for country-level research: they handle missing data, manage temporal correlations, address unbalanced datasets, and model heterogeneity. My latest article compares inequalities across OECD countries using this method: doi.org/10.1163/15691330-bja… #LongitudinalData
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Choose your pandemic fighter: 1. Zionist with Book Deal 2. Epidemiologist with Neck Mask 3. Doctor with Karaoke Mic 4. Professor with Pilsner Beer #longitudinaldata
4% Zio
30% Epi
4% Doc
63% Prof
27 votes • Final results
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In my research on longitudinal data spanning two decades across 27 countries, the Mixed Model for Repeated Measures showed exceptional adaptability, robustness, and effectiveness in managing missing data. #LongitudinalData #MixedModel brill.com/view/journals/coso…

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Despite global crises like the Great Recession and the pandemic, Nordic countries (NM), the Czech Republic, and Austria have maintained the lowest income inequality among OECD countries over the past two decades. #Inequality #LongitudinalData
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We’re kicking off at #DigitalFootprints24 with @_andy_boyd with the first workshop of the day looking at how linkage of #LongitudinalData and #SmartData has the potential to unlock new insights on population behaviours and trends
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Exciting news: @BristolUni and @ucl will be leading the Population Research UK (PRUK) co-ordination hub. Their leadership team includes co-Directors @GoodmanAlissa and @nic_timpson Find out more: orlo.uk/v3Ova #LongitudinalData
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25 Mar 2024
Delighted to be hosting Annette Lareau, Prof of Sociology @SociologyatPenn at #sbarcIspark on 11/04 for a @LeverhulmeTrust lecture: ‘Class, Culture, and Barriers to Mobility’. Find out more: bit.ly/3T8c2YG #qualitativeresearch #longitudinaldata #HEresearch @LSEsociology
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