我有此子数据，并尝试使用lqmm包进行处理。
我的问题是，如果我让模型知道因变量的名称，则模型运行良好。但是，如果我让模型知道变量的位置（要求模型自己查找变量），则它不起作用。更具体地说，y在数据的第一列中。在这里，我建立两个模型：
model_1 <- lqmm(fixed=y~x, random=~1, group=id, data=data, weights=data$weight)
model_2 <- lqmm(fixed= data[,1] ~x, random=~1, group=id, data=data_4, weights=data_4$weight)
model_1工作得很好，但是model_2却没有。
由于我要分析成千上万个因变量。这意味着我要运行数千个模型。因此，我将使用循环功能（或并行功能）让模型一个接一个地运行。
任何人都可以帮助我解决如何解决此问题吗？非常感谢！
下面是我的只有一个因变量的子数据。
structure(list(y = c(0.730650409852947, 0.728216844947554, 0.767963386727689,
0.891327480712956, 0.870997963340122, 0.872775072188941, 0.91635397123202,
0.823406264110669, 0.829918381227682, 0.780403526888554, 0.818116890846328,
0.784000713457594, 0.745812807881773, 0.725237449118046, 0.881360961376787,
0.803437730675946, 0.796654355854877, 0.899503414028554, 0.921515307796896,
0.900906505510132, 0.849416799530083, 0.847148124051182, 0.842549573350339,
0.898004262739779, 0.909744724571248, 0.801824118905529, 0.761721812764623,
0.833628731343284, 0.894758927447442, 0.857694883816786, 0.878278208851706,
0.869254462170273, 0.821706914423926, 0.80044541719464, 0.847700931747595,
0.781347150259067, 0.798202073681888, 0.867736724164886, 0.853367042059297,
0.829895959707364), id = c(14, 14, 18, 22, 22, 22, 23, 25, 25,
25, 26, 26, 27, 27, 28, 33, 33, 37, 37, 37, 47, 47, 47, 54, 54,
64, 64, 72, 72, 78, 80, 80, 88, 88, 100, 100, 100, 101, 101,
101), x = c(49.3220157451866, 49.3220157451866, 57.8198215672973,
36.622903047587, 36.622903047587, 36.622903047587, 43.4323371060975,
49.5278043359919, 49.5278043359919, 49.5278043359919, 48.1232404961316,
48.1232404961316, 31.1127854711425, 31.1127854711425, 37.9682264385375,
44.6286153851752, 44.6286153851752, 32.9579134200441, 32.9579134200441,
32.9579134200441, 43.5192851377132, 43.5192851377132, 43.5192851377132,
41.3467215134667, 41.3467215134667, 50.7958386259009, 50.7958386259009,
42.0390610102311, 42.0390610102311, 50.0178728651761, 37.5973073779753,
37.5973073779753, 37.2517969615217, 37.2517969615217, 50.0489337446737,
50.0489337446737, 50.0489337446737, 34.914930959337, 34.914930959337,
34.914930959337), weight = c(0.940106931323075, 1.27308556092249,
0.985858209365709, 4.16028047821646, 1.60424079874887, 1.04527174260652,
0.978427631147808, 1.07303283776173, 1.51996458961648, 3.69240282395003,
0.973255510970715, 1.87809501604974, 0.998130102291579, 1.42381720181429,
1.15527933102421, 1.02957402938536, 1.31981342276168, 1.22321221901807,
3.17201942074959, 1.13674167341076, 0.984021029075887, 1.36396951412187,
3.78360745964862, 1.27062020454613, 0.940399688689507, 1.27711407280325,
0.983414979063376, 0.957791080709983, 1.29604701913859, 0.873806895526164,
1.18174466417534, 1.0472475515176, 1.68070925571614, 1.21783984541102,
1.13530898254566, 1.38634555990181, 5.2261616, 0.725463234706692,
2.73692073127317, 1.12971495463948)), groups = structure(list(
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答案 0 :(得分：0)
R的公式语法不接受data[,1] ~ x之类的东西。但是，您可以使用formula()，paste()和names()轻松构建公式。假设您有一个data.frame df，而前三列是您要用作线性回归中的因变量的变量；第四列是x变量。这是一种进行方法：
df <- data.frame(
y1 = c(1, 1, 4, 4, 5, 5, 7, 7),
y2 = c(1, 2, 1, 2, 7, 8, 7, 8),
y3 = c(3, 3, 4, 4, 5, 5, 6, 6),
x = c(1, 2, 3, 4, 5, 6, 7, 8)
)
for(i in 1:3) {
form <- formula(paste(names(df)[i], "~ x"))
out <- lm(form, data=df)
print(coef(out))
}