Pinned Repositories
-surveycorrcov-sas-macro
SAS macro for complex survey data to generate correlation, covariance, and sum of squares and crossproducts matrices; presented at SAS Global Forum 2020
adjustedCurves
An R-Package to estimate and plot confounder-adjusted survival curves (single event survival data) and confounder-adjusted cumulative incidence functions (data with competing risks) using various methods.
An-Introduction-to-Statistical-Learning
This repository contains the exercises and its solution contained in the book "An Introduction to Statistical Learning" in python.
android_kernel_xiaomi_whyred
Panda Kernel For Redmi Note 5 Pro(whyred)
BBISR-SAS-Macros
A series of generic SAS® macros to carry out streamlined routine data analyses with reports for observational studies（常用生物统计方法集合）
CNKI-download
:frog: 知网(CNKI)文献下载及文献速览爬虫
cumRoc3
%cumRoc3 is a SAS macro that implements cumulative ROC curve analysis for three-level (ternary) ordinal outcomes
EasyPubMed
EasyPubMed is an extension to make new PubMed easy to use
ggstatsplot
Enhancing `ggplot2` plots with statistical analysis 📊🎨📣(基于ggplot的图形为其添加统计学注释的R包)
interrputed-time-series-analysis
interrupted time series analysis
laoli985's Repositories
laoli985/interrputed-time-series-analysis
interrupted time series analysis
laoli985/-surveycorrcov-sas-macro
SAS macro for complex survey data to generate correlation, covariance, and sum of squares and crossproducts matrices; presented at SAS Global Forum 2020
laoli985/adjustedCurves
An R-Package to estimate and plot confounder-adjusted survival curves (single event survival data) and confounder-adjusted cumulative incidence functions (data with competing risks) using various methods.
laoli985/An-Introduction-to-Statistical-Learning
This repository contains the exercises and its solution contained in the book "An Introduction to Statistical Learning" in python.
laoli985/android_kernel_xiaomi_whyred
Panda Kernel For Redmi Note 5 Pro(whyred)
laoli985/BBISR-SAS-Macros
A series of generic SAS® macros to carry out streamlined routine data analyses with reports for observational studies（常用生物统计方法集合）
laoli985/CNKI-download
:frog: 知网(CNKI)文献下载及文献速览爬虫
laoli985/cumRoc3
%cumRoc3 is a SAS macro that implements cumulative ROC curve analysis for three-level (ternary) ordinal outcomes
laoli985/EasyPubMed
EasyPubMed is an extension to make new PubMed easy to use
laoli985/ggstatsplot
Enhancing `ggplot2` plots with statistical analysis 📊🎨📣(基于ggplot的图形为其添加统计学注释的R包)
laoli985/github-projects-
laoli985/hello-world
laoli985/interesting-python
有趣的Python爬虫和Python数据分析小项目(Some interesting Python crawlers and data analysis projects)
laoli985/lihang-code
《统计学习方法》的代码实现
laoli985/lrt-strat-cox-ph
Likelihood Ratio Test MACRO for the Stratified Cox Proportional Hazards Model
laoli985/MachineLearning
Basic Machine Learning and Deep Learning
laoli985/macrocore
Production quality SAS macros
laoli985/My-SASpgm
Place to store all my SAS programs with academic analysis purpose
laoli985/PING
Library of macro/function utilities developed (R/SAS/Stata) for the implementation of statistical processes in production environments
laoli985/Python-Data-Science-Handbook
A Chinese translation of Jake Vanderplas' "Python Data Science Handbook". 《Python数据科学手册》在线Jupyter notebook中文翻译
laoli985/RepeatedMeasuresCorrelation
SAS macro for estimating the correlation coefficient in repeated measures data
laoli985/sas-1
A collection of SAS Macros that I use and update regularly.
laoli985/SAS-2
Some of my SAS macros
laoli985/SAS-macros-1
SAS macros for statistical analysis in biomedical research and development
laoli985/sas_macros-1
SAS macros
laoli985/SAS_macros-2
laoli985/SAS_Programming
laoli985/sasGlue
A Sas Macro Utility Library
laoli985/saspy
A Python interface module to the SAS System. It works with Linux, Windows, and mainframe SAS. It supports the sas_kernel project (a Jupyter Notebook kernel for SAS) or can be used on its own.
laoli985/saspy-examples
Sample notebooks that show the capabilities of SASPy. Use these for learning and for validating your environment. And contribute your own!