Azeem M. Shaikh

Selected Publications

Finite- and large-sample inference for ranks using multinomial data with an application to ranking political parties

It is common to rank different categories by means of preferences that are revealed through data […]

Sergei Bazylik, Magne Mogstad, Joseph P. Romano, Azeem M. Shaikh, Daniel Wilhelm
18 November 2021 | CWP40/21
Inference for ranks with applications to mobility across neighborhoods and academic achievement across countries

It is often desired to rank different populations according to the value of some feature of […]

Magne Mogstad, Joseph P. Romano, Azeem M. Shaikh, Daniel Wilhelm
9 April 2021 | CWP17/21

Previous version

Inference for ranks with applications to mobility across neighborhoods and academic achievement across countries
Magne Mogstad, Joseph P. Romano, Daniel Wilhelm, Azeem M. Shaikh
16 March 2020 | CWP10/20
Inference for ranks with applications to mobility across neighborhoods and academic achievement across countries

It is often desired to rank different populations according to the value of some feature of […]

Magne Mogstad, Joseph P. Romano, Daniel Wilhelm, Azeem M. Shaikh
16 March 2020 | CWP10/20
The Wild Bootstrap with a Small Number of Large Clusters

This paper studies the properties of the wild bootstrap-based test proposed in Cameron et al. (2008) […]

Ivan A. Canay, Andres Santos, Azeem M. Shaikh
16 August 2019 | CWP40/19

Previous version

The wild bootstrap with a “small” number of “large” clusters
Ivan A. Canay, Andres Santos, Azeem M. Shaikh
11 April 2018 | CWP27/18
Inference in Experiments with Matched Pairs

This paper studies inference for the average treatment effect in randomized controlled trials where treatment status […]

Azeem M. Shaikh, Yuehao Bai, Joseph P. Romano
25 April 2019 | CWP19/19
Inference under covariate-adaptive randomization with multiple treatments

This paper studies inference in randomized controlled trials with covariate-adaptive randomization when there are multiple treatments. […]

Federico A. Bugni, Ivan A. Canay, Azeem M. Shaikh
22 January 2019 | CWP04/19

Previous version

Inference under covariate-adaptive randomization with multiple treatments
Federico A. Bugni, Ivan A. Canay, Azeem M. Shaikh
2 August 2017 | CWP34/17
The wild bootstrap with a “small” number of “large” clusters

This paper studies the properties of the wild bootstrap-based test proposed in Cameron et al. (2008) […]

Ivan A. Canay, Andres Santos, Azeem M. Shaikh
11 April 2018 | CWP27/18

Latest version

The Wild Bootstrap with a Small Number of Large Clusters
Ivan A. Canay, Andres Santos, Azeem M. Shaikh
16 August 2019 | CWP40/19
Inference under covariate-adaptive randomization with multiple treatments

This paper studies inference in randomized controlled trials with covariate-adaptive randomization when there are multiple treatments. […]

Federico A. Bugni, Ivan A. Canay, Azeem M. Shaikh
2 August 2017 | CWP34/17

Latest version

Inference under covariate-adaptive randomization with multiple treatments
Federico A. Bugni, Ivan A. Canay, Azeem M. Shaikh
22 January 2019 | CWP04/19
Inference under covariate-adaptive randomization

This paper studies inference for the average treatment effect in randomized controlled trials with covariate-adaptive randomization. […]

Federico A. Bugni, Ivan A. Canay, Azeem M. Shaikh
24 May 2017 | CWP25/17

Previous version

Inference under covariate-adaptive randomization
Federico A. Bugni, Ivan A. Canay, Azeem M. Shaikh
7 August 2015 | CWP45/15
Inference under Covariate-Adaptive Randomization

This paper studies inference for the average treatment eff ect in randomized controlled trials with covariate-adaptive […]

Federico A. Bugni, Ivan A. Canay, Azeem M. Shaikh
10 May 2016 | CWP21/16

Previous version

Inference under covariate-adaptive randomization
Federico A. Bugni, Ivan A. Canay, Azeem M. Shaikh
7 August 2015 | CWP45/15