Ryan A. Peterson, Emily Slade, Gina‐Maria Pomann, Walter T. Ambrosius
{"title":"与统计学家合作愉快:执业统计学家对其最成功合作的看法","authors":"Ryan A. Peterson, Emily Slade, Gina‐Maria Pomann, Walter T. Ambrosius","doi":"10.1002/sta4.694","DOIUrl":null,"url":null,"abstract":"Statistical collaboration requires statisticians to work and communicate effectively with nonstatisticians, which can be challenging for many reasons. To identify common themes and lessons for working smoothly with nonstatistician collaborators, two focus groups of primarily academic collaborative statisticians were held. We identified qualities of collaborations that tend to yield fruitful relationships and those that tend to yield nothing (or worse, with one or both parties being dissatisfied). The initial goal was to share helpful knowledge and individual experiences that can facilitate more successful collaborative relationships for statisticians who work within academic statistical collaboration units. These findings were used to design a follow‐up survey to collect perspectives from a wider set of practicing statisticians on important qualities to consider when assessing potential collaborations. In this survey of practicing statisticians, we found widespread agreement on many good and bad qualities to promote and discourage, respectively. Interestingly, some negative and positive collaboration qualities were less agreed upon, suggesting that in such cases, a mix‐and‐match approach of domain experts to statisticians could alleviate friction and statistician burnout in team science settings. The perceived importance of some collaboration characteristics differed between faculty and staff, while others depended on experience.","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Working well with statisticians: Perceptions of practicing statisticians on their most successful collaborations\",\"authors\":\"Ryan A. Peterson, Emily Slade, Gina‐Maria Pomann, Walter T. Ambrosius\",\"doi\":\"10.1002/sta4.694\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Statistical collaboration requires statisticians to work and communicate effectively with nonstatisticians, which can be challenging for many reasons. To identify common themes and lessons for working smoothly with nonstatistician collaborators, two focus groups of primarily academic collaborative statisticians were held. We identified qualities of collaborations that tend to yield fruitful relationships and those that tend to yield nothing (or worse, with one or both parties being dissatisfied). The initial goal was to share helpful knowledge and individual experiences that can facilitate more successful collaborative relationships for statisticians who work within academic statistical collaboration units. These findings were used to design a follow‐up survey to collect perspectives from a wider set of practicing statisticians on important qualities to consider when assessing potential collaborations. In this survey of practicing statisticians, we found widespread agreement on many good and bad qualities to promote and discourage, respectively. Interestingly, some negative and positive collaboration qualities were less agreed upon, suggesting that in such cases, a mix‐and‐match approach of domain experts to statisticians could alleviate friction and statistician burnout in team science settings. The perceived importance of some collaboration characteristics differed between faculty and staff, while others depended on experience.\",\"PeriodicalId\":0,\"journal\":{\"name\":\"\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0,\"publicationDate\":\"2024-05-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1002/sta4.694\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1002/sta4.694","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Working well with statisticians: Perceptions of practicing statisticians on their most successful collaborations
Statistical collaboration requires statisticians to work and communicate effectively with nonstatisticians, which can be challenging for many reasons. To identify common themes and lessons for working smoothly with nonstatistician collaborators, two focus groups of primarily academic collaborative statisticians were held. We identified qualities of collaborations that tend to yield fruitful relationships and those that tend to yield nothing (or worse, with one or both parties being dissatisfied). The initial goal was to share helpful knowledge and individual experiences that can facilitate more successful collaborative relationships for statisticians who work within academic statistical collaboration units. These findings were used to design a follow‐up survey to collect perspectives from a wider set of practicing statisticians on important qualities to consider when assessing potential collaborations. In this survey of practicing statisticians, we found widespread agreement on many good and bad qualities to promote and discourage, respectively. Interestingly, some negative and positive collaboration qualities were less agreed upon, suggesting that in such cases, a mix‐and‐match approach of domain experts to statisticians could alleviate friction and statistician burnout in team science settings. The perceived importance of some collaboration characteristics differed between faculty and staff, while others depended on experience.