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Imputing missing data with xUCINET

CHUDING LING All Messages By This Member #6947 Dear all, I used to analyze social network data with UCINET. And recently I am trying to use the xUCINET package to do the analyses considering its flexibility. Now I have a question about imputing missing data with xUCINET. According to Borgatti, Everett, and Johnson (2018): “In the case of symmetric or undirected relations, a simple cure is to fill in any missing rows with the data found in the corresponding column. The assumption is that, if the respondent had been able to answer, they would have listed all the actors that mentioned them. This may not be exactly right, but it will be more accurate than treating the missing values as zeros. UCINET has a command called REPLACENA within Matrix Algebra to do this.” However, in the current version of xUCINET, the xImputeMissingData() function only imputes data with density. I am wondering whether we can manually write some codes in xUCINET to realize the function of REPLACENA in UCINET? If yes, could you please give me an example? Many thanks! ? Best, Chuding
Steve Borgatti All Messages By This Member #6950 开云体育 Chuding, you can make your own replacena. Assume your matrix is called X. Then these lines ? Xt <- t(X) X[is.na(X)] = Xt[is.na(X)] ? will replace your missing rows with their corresponding columns. Note that if you have multiple missing rows, such as 1 and 2, you will still have a missing value for the tie between node 1 and node 2, since neither one responded. ? Note there are more sophisticated methods of imputing network data: ? Krause, R. W., Huisman, M., Steglich, C., & Snijders, T. A. (2018, August). Missing network data a comparison of different imputation methods. In?2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)?(pp. 159-163). IEEE. ? ?nidar?i?, A., Ferligoj, A., & Doreian, P. (2012). Non-response in social networks: The impact of different non-response treatments on the stability of blockmodels.?Social Networks,?34(4), 438-450. ? Stephen P. Borgatti Carol Martin Gatton Chair of Management Gatton College of Business and Economics University of Kentucky ? toggle quoted message Show quoted text From: [email protected] <[email protected]> On Behalf Of CHUDING LING via groups.io Sent: Wednesday, January 25, 2023 06:39 To: [email protected] Subject: [ucinet] Imputing missing data with xUCINET ? CAUTION: External Sender ? Dear all, I used to analyze social network data with UCINET. And recently I am trying to use the xUCINET package to do the analyses considering its flexibility. Now I have a question about imputing missing data with xUCINET. According to Borgatti, Everett, and Johnson (2018): “In the case of symmetric or undirected relations, a simple cure is to fill in any missing rows with the data found in the corresponding column. The assumption is that, if the respondent had been able to answer, they would have listed all the actors that mentioned them. This may not be exactly right, but it will be more accurate than treating the missing values as zeros. UCINET has a command called REPLACENA within Matrix Algebra to do this.” However, in the current version of xUCINET, the xImputeMissingData() function only imputes data with density. I am wondering whether we can manually write some codes in xUCINET to realize the function of REPLACENA in UCINET? If yes, could you please give me an example? Many thanks! ? Best, Chuding
CHUDING LING All Messages By This Member #6952 Thank you Prof. Borgatti! The solution suggested by you works! ? Best, Chuding Steve Borgatti <sborgatti@...> 于2023年1月27日周五 02:36写道： toggle quoted message Show quoted text Chuding, you can make your own replacena. Assume your matrix is called X. Then these lines ? Xt <- t(X) X[(X)] = Xt[(X)] ? will replace your missing rows with their corresponding columns. Note that if you have multiple missing rows, such as 1 and 2, you will still have a missing value for the tie between node 1 and node 2, since neither one responded. ? Note there are more sophisticated methods of imputing network data: ? Krause, R. W., Huisman, M., Steglich, C., & Snijders, T. A. (2018, August). Missing network data a comparison of different imputation methods. In?2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)?(pp. 159-163). IEEE. ? ?nidar?i?, A., Ferligoj, A., & Doreian, P. (2012). Non-response in social networks: The impact of different non-response treatments on the stability of blockmodels.?Social Networks,?34(4), 438-450. ? Stephen P. Borgatti Carol Martin Gatton Chair of Management Gatton College of Business and Economics University of Kentucky ? From: [email protected] <[email protected]> On Behalf Of CHUDING LING via Sent: Wednesday, January 25, 2023 06:39 To: [email protected] Subject: [ucinet] Imputing missing data with xUCINET ? CAUTION: External Sender ? Dear all, I used to analyze social network data with UCINET. And recently I am trying to use the xUCINET package to do the analyses considering its flexibility. Now I have a question about imputing missing data with xUCINET. According to Borgatti, Everett, and Johnson (2018): “In the case of symmetric or undirected relations, a simple cure is to fill in any missing rows with the data found in the corresponding column. The assumption is that, if the respondent had been able to answer, they would have listed all the actors that mentioned them. This may not be exactly right, but it will be more accurate than treating the missing values as zeros. UCINET has a command called REPLACENA within Matrix Algebra to do this.” However, in the current version of xUCINET, the xImputeMissingData() function only imputes data with density. I am wondering whether we can manually write some codes in xUCINET to realize the function of REPLACENA in UCINET? If yes, could you please give me an example? Many thanks! ? Best, Chuding

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