{"payload":{"pageCount":1,"repositories":[{"type":"Public","name":"Epitome","owner":"StatisticsHealthEconomics","isFork":false,"description":"EPITOME project ","allTopics":["statistical-analysis","epidemiology","bayesian-inference","causal-inference","spatio-temporal","policy-making","psychiatric-disorders"],"primaryLanguage":{"name":"JavaScript","color":"#f1e05a"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":0,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-08-05T15:03:54.074Z"}},{"type":"Public","name":"multimcm","owner":"StatisticsHealthEconomics","isFork":false,"description":"Bayesian relative mixture cure modelling with Stan.","allTopics":["stan","hierarchical-models","cure-model"],"primaryLanguage":{"name":"R","color":"#198CE7"},"pullRequestCount":0,"issueCount":14,"starsCount":0,"forksCount":0,"license":"Other","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-08-03T21:51:59.259Z"}},{"type":"Public","name":"ModStanR","owner":"StatisticsHealthEconomics","isFork":false,"description":"An R package for model-based standardisation.","allTopics":["bayesian-inference","population-adjustment"],"primaryLanguage":{"name":"R","color":"#198CE7"},"pullRequestCount":0,"issueCount":9,"starsCount":2,"forksCount":0,"license":"GNU General Public License v3.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-07-29T12:51:24.122Z"}},{"type":"Public","name":"stat0019_binder","owner":"StatisticsHealthEconomics","isFork":false,"description":"This repo is used to create a fully functional Rstudio environment for computation","allTopics":[],"primaryLanguage":{"name":"R","color":"#198CE7"},"pullRequestCount":0,"issueCount":0,"starsCount":3,"forksCount":0,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-07-24T08:24:56.632Z"}},{"type":"Public","name":"blendR","owner":"StatisticsHealthEconomics","isFork":false,"description":"Blended survival analysis ","allTopics":[],"primaryLanguage":{"name":"R","color":"#198CE7"},"pullRequestCount":0,"issueCount":5,"starsCount":1,"forksCount":0,"license":"GNU General Public License v3.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-06-30T17:31:55.228Z"}},{"type":"Public","name":"covid","owner":"StatisticsHealthEconomics","isFork":false,"description":"The project can be split into different sub-projects (easy-medium difficulty: meta-analysis of COVID vaccines; medium-high difficulty: estimating excess mortality due to COVID). Requires skills in R and will require some learning on Bayesian modelling. ","allTopics":["meta-analysis","bayesian-statistics","hierarchical-models","generalised-linear-models","spatio-temporal-analysis"],"primaryLanguage":null,"pullRequestCount":0,"issueCount":0,"starsCount":2,"forksCount":1,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-02-26T16:24:42.318Z"}},{"type":"Public","name":"speed-limits","owner":"StatisticsHealthEconomics","isFork":false,"description":"The project aims at using quasi-experimental designs to estimate the impact of policy reducing speed limits in major cities, on the number of road accidents. It is based on Bayesian hierarchical modelling and Poisson regression","allTopics":["bayesian-inference","hierarchical-models","poisson-regression","road-accidents","speed-limit"],"primaryLanguage":null,"pullRequestCount":0,"issueCount":0,"starsCount":3,"forksCount":0,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-02-01T17:28:35.732Z"}},{"type":"Public","name":"gender-bias-in-hiring","owner":"StatisticsHealthEconomics","isFork":false,"description":"The project can be split into different sub-projects (easy difficulty: replication of the published meta-analysis for evidence of gender bias in hiring decisions; medium for newer modelling). Requires skills in R and will require some learning on Bayesian modelling. ","allTopics":["meta-analysis","binomial-model","bayesian-statistics","generalised-linear-models","gender-bias"],"primaryLanguage":null,"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":0,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-12-04T16:39:41.648Z"}},{"type":"Public","name":"london-bikes","owner":"StatisticsHealthEconomics","isFork":false,"description":"Estimate the relationship between the number of bikes shared around the London network on a given day, depending on weather and other characteristics to predict the capacity needed to satisfy demand at any given point. Requires R and familiarity with non-linear regression models","allTopics":["glm","bayesian-inference","poisson-regression"],"primaryLanguage":null,"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":0,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-11-22T19:57:25.263Z"}},{"type":"Public","name":"blendR-paper","owner":"StatisticsHealthEconomics","isFork":false,"description":"","allTopics":[],"primaryLanguage":{"name":"HTML","color":"#e34c26"},"pullRequestCount":1,"issueCount":1,"starsCount":3,"forksCount":1,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-09-17T22:41:27.570Z"}},{"type":"Public","name":".github","owner":"StatisticsHealthEconomics","isFork":false,"description":"","allTopics":[],"primaryLanguage":null,"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":0,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-05-21T10:31:13.577Z"}},{"type":"Public","name":"BayesianMixtureCure","owner":"StatisticsHealthEconomics","isFork":false,"description":"Bayesian Mixture Cure Modelling in Stan","allTopics":[],"primaryLanguage":{"name":"Stan","color":"#b2011d"},"pullRequestCount":0,"issueCount":1,"starsCount":4,"forksCount":2,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-01-11T16:30:31.525Z"}},{"type":"Public","name":"Polished-Fribble","owner":"StatisticsHealthEconomics","isFork":true,"description":"Login system for stats department","allTopics":[],"primaryLanguage":{"name":"R","color":"#198CE7"},"pullRequestCount":0,"issueCount":0,"starsCount":2,"forksCount":5,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2021-02-05T11:06:39.006Z"}},{"type":"Public","name":"HTAinRmanifesto","owner":"StatisticsHealthEconomics","isFork":false,"description":"","allTopics":[],"primaryLanguage":{"name":"R","color":"#198CE7"},"pullRequestCount":0,"issueCount":5,"starsCount":4,"forksCount":1,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-12-10T09:21:35.255Z"}},{"type":"Public","name":"COVID_Italy","owner":"StatisticsHealthEconomics","isFork":false,"description":"Data on mortality in Italy for the PLOS paper","allTopics":[],"primaryLanguage":{"name":"R","color":"#198CE7"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":0,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-10-13T22:01:15.765Z"}},{"type":"Public","name":"STAT0019-practicals","owner":"StatisticsHealthEconomics","isFork":false,"description":"","allTopics":[],"primaryLanguage":{"name":"R","color":"#198CE7"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":0,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-09-30T11:10:36.152Z"}}],"repositoryCount":16,"userInfo":null,"searchable":true,"definitions":[],"typeFilters":[{"id":"all","text":"All"},{"id":"public","text":"Public"},{"id":"source","text":"Sources"},{"id":"fork","text":"Forks"},{"id":"archived","text":"Archived"},{"id":"template","text":"Templates"}],"compactMode":false},"title":"StatisticsHealthEconomics repositories"}