Mentions
Extended reach
Total likes
Video views
AI synopsis
The discussions highlight appreciation for the detailed breakdown of estimators, such as Huang and Li’s work, and mention practical tools like SPSS add-ons, which indicate an intent to apply the research. The tone is slightly technical and pragmatic, emphasizing the article's relevance to statistical methods and its practical implications for researchers working with small clusters.
Most discussions acknowledge the importance of the methods described in the publication, supporting its validity.
Participants show moderate interest, referencing specific techniques and calling attention to tools and explanations provided in the article.
Posts demonstrate some level of engagement by sharing insights and mentioning practical applications, though not in-depth.
The discussions suggest that the article influences opinions on the importance of proper statistical analysis in group-randomized trials, especially regarding standard errors and small sample corrections.
Reading about cluster-robust SE's and appreciated Huang and Li (2021) breaking down the sandwich estimators into the "meat" and "bread" components. https://t.co/cSeiRKb6X9 https://t.co/RtIhl6iaqw
Use SPSS and want an easy (and free) way to get cluster robust standard errors (that are effective with even 10 clusters)? Check out: https://t.co/S8VgUz2dsg
RT @flhuang: Use SPSS and want an easy (and free) way to get cluster robust standard errors (that are effective with even 10 clusters)? Che…
RT @schotz: Reading about cluster-robust SE's and appreciated Huang and Li (2021) breaking down the sandwich estimators into the "meat" and…
RT @flhuang: Use SPSS and want an easy (and free) way to get cluster robust standard errors (that are effective with even 10 clusters)? Che…
RT @flhuang: Use SPSS and want an easy (and free) way to get cluster robust standard errors (that are effective with even 10 clusters)? Che…
This video demonstrates how you can perform regression analysis involving panel data using SPSS. Specifically, it demonstrates use of the least squares dummy variable LSDV approach to address clustering and includes a…
This video explains how to install Huang's 2020 SPSS macro for generating cluster-robust standard errors, vital for analyzing group-randomized trials with few clusters. The macro improves accuracy with small sample…
RT @schotz: Reading about cluster-robust SE's and appreciated Huang and Li (2021) breaking down the sandwich estimators into the "meat" and…
Reading about cluster-robust SE's and appreciated Huang and Li (2021) breaking down the sandwich estimators into the "meat" and "bread" components. https://t.co/cSeiRKb6X9 https://t.co/RtIhl6iaqw
RT @flhuang: Use SPSS and want an easy (and free) way to get cluster robust standard errors (that are effective with even 10 clusters)? Che…
RT @flhuang: Use SPSS and want an easy (and free) way to get cluster robust standard errors (that are effective with even 10 clusters)? Che…
RT @flhuang: Use SPSS and want an easy (and free) way to get cluster robust standard errors (that are effective with even 10 clusters)? Che…
Use SPSS and want an easy (and free) way to get cluster robust standard errors (that are effective with even 10 clusters)? Check out: https://t.co/S8VgUz2dsg