Random forest
randomForestSRC: Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
https://cran.r-project.org/web/packages/randomForestSRC/randomForestSRC.pdf[개발자의 시선으로 보는 머신러닝 2-1편] 랜덤 포레스트로 예측, 분류 한번씩 해보기
https://cholol.tistory.com/493?category=803480Random Survival Forests • Fast Unified Random Forests with randomForestSRC
https://www.randomforestsrc.org/articles/survival.htmlRandom survival forests for dynamic predictions of a time-to-event outcome using a longitudinal biomarker | BMC Medical Research Methodology | Full Text
https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-021-01375-x
통계기법
제 12 장 일반화 선형모형 | 회귀모형 이론과 계산
https://ilovedata.github.io/teaching/linearmodel-grad/_book/chapglm.htmlFrontiers | Mediation Analysis with Survival Outcomes: Accelerated Failure Time vs. Proportional Hazards Models | Psychology
https://www.frontiersin.org/articles/10.3389/fpsyg.2016.00423/fullGitHub - anddis/med4way: Stata command for the 4-way decomposition using parametric regression models
https://github.com/anddis/med4way
기타
FAQ: summarize and aweights and pweights | Stata
https://www.stata.com/support/faqs/statistics/weights-and-summary-statistics/어떻게 R 속도를 높일 수 있을까
https://brunch.co.kr/@qqplot/101회귀분석 - 모형 변환(대수변환 및 역변환의 지수와 로그) + 가중회귀분석
https://bluenoa.tistory.com/47통계기초(빈도주의와 베이지안)
https://hun931018.tistory.com/41이 땅, 통계학의 오늘① - BI KOREA
http://www.bikorea.net/news/articleView.html?idxno=4616통계용어 1 페이지 | 사단법인 한국통계학회
https://www.kss.or.kr/bbs/board.php?bo_table=psd_sec
Survival tree
Using R to calculate survival probabilities with time-varying covariates using an Andersen-Gill model - Cross Validated
https://stats.stackexchange.com/questions/200252/using-r-to-calculate-survival-probabilities-with-time-varying-covariates-using-aGitHub - weichiyao/TimeVaryingData_LTRCforests
https://github.com/weichiyao/TimeVaryingData_LTRCforestsLTRCART function - RDocumentation
https://www.rdocumentation.org/packages/LTRCtrees/versions/1.1.1/topics/LTRCARTRPubs - Decision Trees and Random Forests
https://rpubs.com/twyunting/Decision_Trees_and_Random_ForestsxwMOOC 모형
http://aispiration.com/model/model_survival_tree.htmlSurvival trees for left-truncated and right-censored data, with application to time-varying covariate data | Biostatistics | Oxford Academic
https://academic.oup.com/biostatistics/article/18/2/352/2739324Time-To-Event (TTE) Data Analysis | Columbia Public Health
https://www.publichealth.columbia.edu/research/population-health-methods/time-event-data-analysisUsage of R package LTRCtrees
https://cran.r-project.org/web/packages/LTRCtrees/vignettes/LTRCtrees.htmlPredictive Evaluation Metrics in Survival Analysis
https://cran.r-project.org/web/packages/SurvMetrics/vignettes/SurvMetrics-vignette.htmlRPubs - 생존나무분석
https://rpubs.com/cardiomoon/70724Survival Analysis in R - YouTube
https://www.youtube.com/watch?v=Bubo_7R7h0Qhttps://stefvanbuuren.name/fimd/sec-cart.html
https://stefvanbuuren.name/fimd/sec-cart.html
imputation
랜덤포레스트 모델의 결측값 대체 방법
https://aimb.tistory.com/14016.6 Application | A Guide on Data Analysis
https://bookdown.org/mike/data_analysis/application-10.html#missforestR Packages | Impute Missing Values In R
https://www.analyticsvidhya.com/blog/2016/03/tutorial-powerful-packages-imputing-missing-values/
Sequence Analysis
Clustering의 Distance Measure (Euclidean distance, Hamming distance, Jaccard distance) - 유니의 공부
https://process-mining.tistory.com/121VOSS-Sequencing-Toolkit/creating_multichannel_object.R at master · aronlindberg/VOSS-Sequencing-Toolkit · GitHub
https://github.com/aronlindberg/VOSS-Sequencing-Toolkit/blob/master/creating_multichannel_object.RSocial Sequence Analysis: An Overview - YouTube
https://www.youtube.com/watch?v=9WJPook9QscRPubs - Doing Sequence Analysis
https://rpubs.com/Kolpashnikova/sequenceAnalysis
STATA
logit, vce(cluster) vs xtlogit, fe: coefficients' sign and r-squared - Statalist
https://www.statalist.org/forums/forum/general-stata-discussion/general/1421504-logit-vce-cluster-vs-xtlogit-fe-coefficients-sign-and-r-squared
미분류
고정효과(fixed effect)와 임의효과(random effect) – 숨은원리 데이터사이언스
http://ds.sumeun.org/?p=1923[개념 통계 16] 모집단분포와 표본분포란 무엇인가?
https://drhongdatanote.tistory.com/54Orange Data Mining - Workflows
https://orangedatamining.com/workflows/[천경록의 수식 없는 통계학] 의사결정트리의 원리 < AI < 기사본문 - 경영자를 위한 디지털 전략 가이드, 스마투스 비즈니스 리뷰
http://www.sbr.ai/news/articleView.html?idxno=1583의사결정나무(Decision Tree) · ratsgo's blog
https://ratsgo.github.io/machine%20learning/2017/03/26/treepalettes - Color palettes, symbol palettes, and line pattern palettes for Stata graphs
http://repec.sowi.unibe.ch/stata/palettes/index.html[Mplus] 다층모형(Multilevel Modeling) syntax 설명(1)
https://graduationplease.tistory.com/86?category=823207패널데이터 분석 (3) : 고정효과모형(Fixed effect Model) : 네이버 블로그
https://m.blog.naver.com/PostView.naver?blogId=s2ak74&logNo=221263661861&targetKeyword=&targetRecommendationCode=1Understanding the Bias-Variance Tradeoff | by Seema Singh | Towards Data Science
https://towardsdatascience.com/understanding-the-bias-variance-tradeoff-165e6942b229SOVIDENCE :: SPSS의 가중치 문제
https://sovidence.tistory.com/1039Data Preparation and Coding – UW-CTRI – UW–Madison
https://ctri.wisc.edu/researchers/behavior-change-analysis/data-preparation-and-coding/