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Statistics版 - ROC: multiple measurements for each subject?
相关主题
请教:SAS 处理Repeated Measurement的问题问大家一个repeated measure的问题
请教如何用proc glimmix 分析 repeated measures with binary outcome.How to express cut-off value
怎么样能够把实验点的uncertainty包括到线性拟和出来的参数里? (转载)Another question about ROC
请问各位大牛 当regressor/covariates 是random的时候 怎么estimate啊?ROC Analysis - help needed!
请教个最基本的repeated measure[合集] 如果对两组时间序列进行相关分析
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请教一个PROC MIXED做REPEATED MEASUREMENT问题如何使模型stable?
请教个比较slope的问题——包子贴Re: what is errors-in-variables fit?
相关话题的讨论汇总
话题: roc话题: subject话题: each话题: multiple
进入Statistics版参与讨论
1 (共1页)
w******8
发帖数: 59
1
Here we have N subjects, each subject having a few times of measurement of a
predictor X and a outcome variable Y (binary).
If each subject were measured only once I could have done a ROC curve to see
if X has any prediction value for Y, but since now each subject is having
multiple measurements (from different time point), is it possible to do a
ROC analysis?
Thanks!
P****D
发帖数: 11146
w******8
发帖数: 59
3
Here we have N subjects, each subject having a few times of measurement of a
predictor X and a outcome variable Y (binary).
If each subject were measured only once I could have done a ROC curve to see
if X has any prediction value for Y, but since now each subject is having
multiple measurements (from different time point), is it possible to do a
ROC analysis?
Thanks!
P****D
发帖数: 11146
w******4
发帖数: 488
5
比较简单一些的做法是对每一个subject根据repeated measure算出一个值(指标),
可以是mean, median, iqr etc., 然后根据这个值去预测y, 画出ROC
1 (共1页)
进入Statistics版参与讨论
相关主题
Re: what is errors-in-variables fit?请教个最基本的repeated measure
[合集] 请教一个统计分析问题问题:fitness in categorical regression
生统申请求教请教一个PROC MIXED做REPEATED MEASUREMENT问题
想学data mining和machine learning 请问哪些课比较重要?请教个比较slope的问题——包子贴
请教:SAS 处理Repeated Measurement的问题问大家一个repeated measure的问题
请教如何用proc glimmix 分析 repeated measures with binary outcome.How to express cut-off value
怎么样能够把实验点的uncertainty包括到线性拟和出来的参数里? (转载)Another question about ROC
请问各位大牛 当regressor/covariates 是random的时候 怎么estimate啊?ROC Analysis - help needed!
相关话题的讨论汇总
话题: roc话题: subject话题: each话题: multiple