#confounder — Public Fediverse posts

'Data-driven Automated Negative Control Estimation (DANCE): Search for, Validation of, and Causal Inference with Negative Controls', by Erich Kummerfeld, Jaewon Lim, Xu Shi.

http://jmlr.org/papers/v25/22-1062.html

#confounder #causal #confounding

'Data-driven Automated Negative Control Estimation (DANCE): Search for, Validation of, and Causal Inference with Negative Controls', by Erich Kummerfeld, Jaewon Lim, Xu Shi.

http://jmlr.org/papers/v25/22-1062.html

#confounder #causal #confounding

'Data-driven Automated Negative Control Estimation (DANCE): Search for, Validation of, and Causal Inference with Negative Controls', by Erich Kummerfeld, Jaewon Lim, Xu Shi.

http://jmlr.org/papers/v25/22-1062.html

#confounder #causal #confounding

'Data-driven Automated Negative Control Estimation (DANCE): Search for, Validation of, and Causal Inference with Negative Controls', by Erich Kummerfeld, Jaewon Lim, Xu Shi.

http://jmlr.org/papers/v25/22-1062.html

#confounder #causal #confounding

'Data-driven Automated Negative Control Estimation (DANCE): Search for, Validation of, and Causal Inference with Negative Controls', by Erich Kummerfeld, Jaewon Lim, Xu Shi.

http://jmlr.org/papers/v25/22-1062.html

#confounder #causal #confounding

'Naive regression requires weaker assumptions than factor models to adjust for multiple cause confounding', by Justin Grimmer, Dean Knox, Brandon Stewart.

http://jmlr.org/papers/v24/21-0515.html

#confounders #confounder #causally

'Naive regression requires weaker assumptions than factor models to adjust for multiple cause confounding', by Justin Grimmer, Dean Knox, Brandon Stewart.

http://jmlr.org/papers/v24/21-0515.html

#confounders #confounder #causally

'Naive regression requires weaker assumptions than factor models to adjust for multiple cause confounding', by Justin Grimmer, Dean Knox, Brandon Stewart.

http://jmlr.org/papers/v24/21-0515.html

#confounders #confounder #causally

'Naive regression requires weaker assumptions than factor models to adjust for multiple cause confounding', by Justin Grimmer, Dean Knox, Brandon Stewart.

http://jmlr.org/papers/v24/21-0515.html

#confounders #confounder #causally

'Naive regression requires weaker assumptions than factor models to adjust for multiple cause confounding', by Justin Grimmer, Dean Knox, Brandon Stewart.

http://jmlr.org/papers/v24/21-0515.html

#confounders #confounder #causally

2) #Confounder
In statistics, a confounder is a #variable that influences both the #independent and #dependent variable - and thus creates a false #correlation between these two variables.

2) #Confounder
In statistics, a confounder is a #variable that influences both the #independent and #dependent variable - and thus creates a false #correlation between these two variables.

2) #Confounder
In statistics, a confounder is a #variable that influences both the #independent and #dependent variable - and thus creates a false #correlation between these two variables.

#Data4GoodMonday
This week: What is a confounder?
Read in 🧵!

#data4good #datascience #dataforgood #data4goodmonday #störfaktor #confounder

#Data4GoodMonday
This week: What is a confounder?
Read in 🧵!

#data4good #datascience #dataforgood #data4goodmonday #störfaktor #confounder

#Data4GoodMonday
This week: What is a confounder?
Read in 🧵!

#data4good #datascience #dataforgood #data4goodmonday #störfaktor #confounder