我已经在 lme4 包中为 r 建立并运行了一个混合效应逻辑回归模型,以估计不同位置(细胞/栖息地)中鱼类的占用概率。数据框由 68 条个体鱼的 1,207,140 个观测值组成。对于每个人(每天约 1 年),它描述了每个唯一位置的出现次数相对于所有位置的出现总数。
这是基本模型:
m.base = glmer(cbind(N,t.move-N) ~ jdate + snSurface.Area + Restoration..P.A. +
Release.Location+ Sex + (1|Station) + (0 + jdate|ID), data=allfishdat, family=binomial)
where N=# unique positions, t.move=total positions, jdate=julian date, Station=locations, ID=fish ID
我收到以下警告消息:
Warning messages:
1: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model failed to converge with max|grad| = 3349.26 (tol = 0.001)
2: In if (resHess$code != 0) { :
the condition has length > 1 and only the first element will be used
3: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model is nearly unidentifiable: very large eigenvalue
- Rescale variables?;Model is nearly unidentifiable: large eigenvalue ratio
- Rescale variables?
我进行了一些搜索以试图了解这些消息的含义及其对模型的影响,但还没有理解这些警告。