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The Frisch–Waugh–Lovell theorem for standard errors. (2021). Ding, Peng.
In: Statistics & Probability Letters.
RePEc:eee:stapro:v:168:y:2021:i:c:s0167715220302480.

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  1. From Replications to Revelations: Heteroskedasticity-Robust Inference. (2024). Kranz, Sebastian.
    In: MPRA Paper.
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  2. Frisch–Waugh–Lovell theorem-type results for the k-Class and 2SGMM estimators. (2024). Basu, Deepankar.
    In: Statistics & Probability Letters.
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  3. No star is good news: A unified look at rerandomization based on p-values from covariate balance tests. (2024). Ding, Peng ; Zhao, Anqi.
    In: Journal of Econometrics.
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  4. The Yule-Frisch-Waugh-Lovell Theorem for Linear Instrumental Variables Estimation. (2023). Basu, Deepankar.
    In: Papers.
    RePEc:arx:papers:2307.12731.

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  5. The Yule-Frisch-Waugh-Lovell Theorem. (2023). Basu, Deepankar.
    In: Papers.
    RePEc:arx:papers:2307.00369.

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  6. Peng Ding’s contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes. (2022). Ding, Peng.
    In: Journal of the Royal Statistical Society Series B.
    RePEc:bla:jorssb:v:84:y:2022:i:3:p:691-693.

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  7. Two seemingly paradoxical results in linear models: the variance inflation factor and the analysis of covariance. (2021). Peng, Ding.
    In: Journal of Causal Inference.
    RePEc:bpj:causin:v:9:y:2021:i:1:p:1-8:n:1.

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References

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