作者danny789 (这其中一定有什麽误会)
看板Statistics
标题Re: [问题] SEM用PLS跑的问题与优缺点?
时间Tue May 12 22:57:22 2009
※ 引述《chenyutn (人生要死,何为苦心。)》之铭言:
: 标题: Re: [问题] SEM用PLS跑的问题与优缺点?
: 时间: Tue May 12 14:01:33 2009
:
: : 推 chenyutn:bootstrap大约一千次就很足够了 05/11 22:53
: : → chenyutn:毕竟现在电脑跑得很快啊 05/11 22:53
: : → danny789:老实说我有作过实验resample设300-1000差异不大,并不是电 05/12 08:31
: : → danny789:脑速度的问题,而且在MIS领域我真没看过设1000的paper 05/12 08:33
: : → danny789:所以resample并不是设越大越好,也必须有文献支持吧? 05/12 08:34
:
: 想说乾脆回文好了XD
:
: Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies
: for assessing and comparing indirect effects in multiple mediator models
:
: 这是其中的一段:
:
: There is no consensus as to how many bootstrap samples should
: be generated, except that more is better. Given that the percentile end-
: points are estimated using extremes of the sampling distribution and
: that, for BCa intervals, a good estimate of the acceleration constant
: is needed, it is important to minimize sampling variance in these es-
: timates. We recommend at least 5,000 resamples for final reporting,
: although 1,000 is probably sufficient for preliminary analyses. There
: is little reason to use fewer, given the speed of today’s desktop comput-
: ing technology.
:
: 这段也是我的立论基础,虽然在数字设定多少才算大方面仍没有立论,但resample
: 的确是设越大越好。
:
: 我想,这应该不会因传播或MIS领域不同而变吧?
:
: 还是说,有别的研究者有不同意见的?由於我是传播领域的,所以看的多半是传播
: 类的paper,但这几篇都有讨论到resample数,不知道其他领域(例如统计)的paper
: 是不是也有讨论到,而有不同意见?
关於 resample 是不是设越大越好? 其实我找不到文献支持, 所以我也不敢评论.
并且 Behavior Research Methods 是否是该领域不错的 Journal 我也不懂
不过我用 ABI/INFORM Global 及 ScienceDirect (SDOL/SDOS) 都查无此
Journal title 不知何因 ?
还有此篇右下角有学术期刊所没有的 "Copyright 2008 Psychonomic Society, Inc."
不知道这是指什麽?
关於这篇文献(Preacher, 2008)的网路 pdf, 我初略的看了一下内容
我对此篇探讨 PLS 而没有提到 chin 感到有点疑惑, 当然也不是一定要引用 chin
只是有点怪
不知道是否有其他比较强(多)的证据或文献可以证明 resample size 设越大越好?
以下引用 chin(2001)的 PLS-Graph User's Guide 内容片段
(已有 MIS 领域不错的 Journal paper 引用)
The default Bootstrap options are 100 resamples with each sample consisting of the same number of
cases as your original sample set. The bootstrap procedure samples with replacement from your
original sample set. It continues to sample until it reaches the number of cases you specify (or the
default). This procedure is repeated until it reaches the number of bootstrap resamples you specify (or
the default of 100). In general, resamples of 200 tend to provide reasonable standard error estimates.
以下是快速找到的几篇 MIS papers
Resample = 100
Henry, R.M., McCray, G.E., Purvis, R.L. Roberts, T.L. (2007) "Exploiting Organizational Knowledge in Developing IS Project Cost and Schedule Estimates: An Empirical Study", Information & Management, Vol. 44 No.6, pp.598-612.
Resample = 500
Ko, D., Kirsch, J.L., King, W.R. (2005) "Antecedents of knowledge transfer from consultants to clients in enterprise system implementations", MIS Quarterly, Vol. 29 No.1, pp.59-85.
Resample = 100 & 500
Goodhue, D., Lewis, W., and Thompson, R., (2007) "Statistical Power in Analyzing Interaction Effects: Questioning the Advantage of PLS With Product Indicators", Information Systems Research, Vol. 18 No.2, pp.211-227.
也许 Goodhue et al.(2007) 这篇是答案, 但我找不到 pdf 档可以看(汗)
※ 编辑: danny789 来自: 122.254.33.185 (05/12 23:00)
1F:→ bmka:这个问题没那麽复杂吧,先把bootstrap方法原理弄懂 05/12 23:01
2F:→ bmka:resample 数目当然越大越好,至於要多大,那要看data distribut 05/12 23:03
3F:→ bmka:跑久一点不会吃亏的 05/12 23:04