{"title":"Interpreting model coefficients from regression analysis","authors":"Christopher Edwards","doi":"10.1002/sono.12307","DOIUrl":null,"url":null,"abstract":"current analysis, it is not clear that the number of operators and/or the presence of pathology predicts scan time, a subtle but essential difference. This may be the case but is not shown by the statistical analysis used. The authors would benefit by reassessing the types of variables used in the study and analysing their data using the GLM function in SPSS, which can investigate the actual effect between groups. The interpretation would be slightly different, as the output of this type of analysis provides coefficients with respect to a reference group (dummy variable). That is, the difference in scan time compared to one operator or the absence of pathology. So reporting the finding would follow something like ‘ when two operators attended the scan, on average, scan time increased by XX mins (95% CI: X (cid:1) X mins) compared to a single operator, after adjusting for the presence of pathology. ’ I hope this letter is of some assistance to the authors.","PeriodicalId":29898,"journal":{"name":"Sonography","volume":"26 1","pages":""},"PeriodicalIF":0.4000,"publicationDate":"2022-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sonography","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/sono.12307","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0
Abstract
current analysis, it is not clear that the number of operators and/or the presence of pathology predicts scan time, a subtle but essential difference. This may be the case but is not shown by the statistical analysis used. The authors would benefit by reassessing the types of variables used in the study and analysing their data using the GLM function in SPSS, which can investigate the actual effect between groups. The interpretation would be slightly different, as the output of this type of analysis provides coefficients with respect to a reference group (dummy variable). That is, the difference in scan time compared to one operator or the absence of pathology. So reporting the finding would follow something like ‘ when two operators attended the scan, on average, scan time increased by XX mins (95% CI: X (cid:1) X mins) compared to a single operator, after adjusting for the presence of pathology. ’ I hope this letter is of some assistance to the authors.
目前的分析还不清楚手术人员的数量和/或病理的存在是否能预测扫描时间,这是一个微妙但本质的区别。这可能是事实,但所使用的统计分析并没有显示出来。作者将受益于重新评估研究中使用的变量类型,并使用SPSS中的GLM函数分析他们的数据,该函数可以调查组之间的实际影响。解释将略有不同,因为这种分析的输出提供了相对于参考组(虚拟变量)的系数。也就是说,与一个操作员相比,扫描时间的差异或病理的缺失。因此,报告发现将遵循类似于“当两名操作员参加扫描时,在调整病理存在后,扫描时间平均比单个操作员增加XX分钟(95% CI: X (cid:1) X分钟)。”“我希望这封信对作者有所帮助。