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人大经济论坛 › 论坛 › 数据科学与人工智能 › 数据分析与数据科学 › SPSS论坛 › 急问这个多项logit模型的结果是啥意思

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楼主: wwlovell

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[问答] 急问这个多项logit模型的结果是啥意思 [推广有奖]

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wwlovell 发表于 2011-9-29 18:57:10 |只看作者 |坛友微信交流群|倒序 |AI写论文

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参数						95% 置信区间
		估计	标准误	Z	Sig.	下限	上限
常量	[VAR00002 = 0] * [VAR00003 = 0] * [VAR00004 = 0] * [VAR00005 = 0]	-.693a
	[VAR00002 = 0] * [VAR00003 = 0] * [VAR00004 = 0] * [VAR00005 = 1]	-.693a
	[VAR00002 = 0] * [VAR00003 = 0] * [VAR00004 = 1] * [VAR00005 = 0]	-.693a
	[VAR00002 = 0] * [VAR00003 = 0] * [VAR00004 = 1] * [VAR00005 = 1]	-.693a
	[VAR00002 = 0] * [VAR00003 = 1] * [VAR00004 = 0] * [VAR00005 = 0]	-.693a
	[VAR00002 = 0] * [VAR00003 = 1] * [VAR00004 = 0] * [VAR00005 = 1]	-.693a
	[VAR00002 = 0] * [VAR00003 = 1] * [VAR00004 = 1] * [VAR00005 = 0]	-.693a
	[VAR00002 = 0] * [VAR00003 = 1] * [VAR00004 = 1] * [VAR00005 = 1]	-.693a
	[VAR00002 = 1] * [VAR00003 = 0] * [VAR00004 = 0] * [VAR00005 = 0]	-.693a
	[VAR00002 = 1] * [VAR00003 = 0] * [VAR00004 = 0] * [VAR00005 = 1]	-.693a
	[VAR00002 = 1] * [VAR00003 = 0] * [VAR00004 = 1] * [VAR00005 = 0]	-.693a
	[VAR00002 = 1] * [VAR00003 = 0] * [VAR00004 = 1] * [VAR00005 = 1]	2.970a
	[VAR00002 = 1] * [VAR00003 = 1] * [VAR00004 = 0] * [VAR00005 = 0]	-.693a
	[VAR00002 = 1] * [VAR00003 = 1] * [VAR00004 = 0] * [VAR00005 = 1]	-.693a
	[VAR00002 = 1] * [VAR00003 = 1] * [VAR00004 = 1] * [VAR00005 = 0]	-.693a
	[VAR00002 = 1] * [VAR00003 = 1] * [VAR00004 = 1] * [VAR00005 = 1]	2.803a
[VAR00001 = 1]		-3.497	1.435	-2.436	0.015	-6.31	-0.683
[VAR00001 = 2]		-0.932	0.463	-2.012	0.044	-1.839	-0.024
[VAR00001 = 3]		0b	.	.	.	.	.
[VAR00001 = 1] * [VAR00002 = 0]		3.497	2.462	1.42	0.156	-1.329	8.322
[VAR00001 = 1] * [VAR00002 = 1]		0b	.	.	.	.	.
[VAR00001 = 2] * [VAR00002 = 0]		0.932	2.053	0.454	0.65	-3.092	4.955
[VAR00001 = 2] * [VAR00002 = 1]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00002 = 0]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00002 = 1]		0b	.	.	.	.	.
[VAR00001 = 1] * [VAR00003 = 0]		-0.167	2.028	-0.082	0.934	-4.141	3.807
[VAR00001 = 1] * [VAR00003 = 1]		0b	.	.	.	.	.
[VAR00001 = 2] * [VAR00003 = 0]		-0.334	0.669	-0.499	0.617	-1.645	0.977
[VAR00001 = 2] * [VAR00003 = 1]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00003 = 0]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00003 = 1]		0b	.	.	.	.	.
[VAR00001 = 1] * [VAR00004 = 0]		8.292	2.019	4.107	0	4.335	12.25
[VAR00001 = 1] * [VAR00004 = 1]		0b	.	.	.	.	.
[VAR00001 = 2] * [VAR00004 = 0]		4.227	1.513	2.795	0.005	1.263	7.192
[VAR00001 = 2] * [VAR00004 = 1]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00004 = 0]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00004 = 1]		0b	.	.	.	.	.
[VAR00001 = 1] * [VAR00005 = 0]		3.497	2.462	1.42	0.156	-1.329	8.322
[VAR00001 = 1] * [VAR00005 = 1]		0b	.	.	.	.	.
[VAR00001 = 2] * [VAR00005 = 0]		0.932	2.053	0.454	0.65	-3.092	4.955
[VAR00001 = 2] * [VAR00005 = 1]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00005 = 0]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00005 = 1]		0b	.	.	.	.	.
[VAR00001 = 1] * [VAR00002 = 0] * [VAR00003 = 0]		0.167	3.48	0.048	0.962	-6.654	6.988
[VAR00001 = 1] * [VAR00002 = 0] * [VAR00003 = 1]		0b	.	.	.	.	.
[VAR00001 = 1] * [VAR00002 = 1] * [VAR00003 = 0]		0b	.	.	.	.	.
[VAR00001 = 1] * [VAR00002 = 1] * [VAR00003 = 1]		0b	.	.	.	.	.
[VAR00001 = 2] * [VAR00002 = 0] * [VAR00003 = 0]		3.701	2.553	1.45	0.147	-1.302	8.705
[VAR00001 = 2] * [VAR00002 = 0] * [VAR00003 = 1]		0b	.	.	.	.	.
[VAR00001 = 2] * [VAR00002 = 1] * [VAR00003 = 0]		0b	.	.	.	.	.
[VAR00001 = 2] * [VAR00002 = 1] * [VAR00003 = 1]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00002 = 0] * [VAR00003 = 0]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00002 = 0] * [VAR00003 = 1]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00002 = 1] * [VAR00003 = 0]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00002 = 1] * [VAR00003 = 1]		0b	.	.	.	.	.
[VAR00001 = 1] * [VAR00002 = 0] * [VAR00004 = 0]		-8.292	3.475	-2.386	0.017	-15.104	-1.481
[VAR00001 = 1] * [VAR00002 = 0] * [VAR00004 = 1]		0b	.	.	.	.	.
[VAR00001 = 1] * [VAR00002 = 1] * [VAR00004 = 0]		0b	.	.	.	.	.
[VAR00001 = 1] * [VAR00002 = 1] * [VAR00004 = 1]		0b	.	.	.	.	.
[VAR00001 = 2] * [VAR00002 = 0] * [VAR00004 = 0]		-4.227	3.208	-1.318	0.188	-10.514	2.059
[VAR00001 = 2] * [VAR00002 = 0] * [VAR00004 = 1]		0b	.	.	.	.	.
[VAR00001 = 2] * [VAR00002 = 1] * [VAR00004 = 0]		0b	.	.	.	.	.
[VAR00001 = 2] * [VAR00002 = 1] * [VAR00004 = 1]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00002 = 0] * [VAR00004 = 0]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00002 = 0] * [VAR00004 = 1]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00002 = 1] * [VAR00004 = 0]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00002 = 1] * [VAR00004 = 1]		0b	.	.	.	.	.
[VAR00001 = 1] * [VAR00002 = 0] * [VAR00005 = 0]		-3.497	3.75	-0.932	0.351	-10.846	3.853
[VAR00001 = 1] * [VAR00002 = 0] * [VAR00005 = 1]		0b	.	.	.	.	.
[VAR00001 = 1] * [VAR00002 = 1] * [VAR00005 = 0]		0b	.	.	.	.	.
[VAR00001 = 1] * [VAR00002 = 1] * [VAR00005 = 1]		0b	.	.	.	.	.
[VAR00001 = 2] * [VAR00002 = 0] * [VAR00005 = 0]		-0.932	3.495	-0.267	0.79	-7.781	5.918
[VAR00001 = 2] * [VAR00002 = 0] * [VAR00005 = 1]		0b	.	.	.	.	.
[VAR00001 = 2] * [VAR00002 = 1] * [VAR00005 = 0]		0b	.	.	.	.	.
[VAR00001 = 2] * [VAR00002 = 1] * [VAR00005 = 1]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00002 = 0] * [VAR00005 = 0]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00002 = 0] * [VAR00005 = 1]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00002 = 1] * [VAR00005 = 0]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00002 = 1] * [VAR00005 = 1]		0b	.	.	.	.	.
[VAR00001 = 1] * [VAR00003 = 0] * [VAR00004 = 0]		-0.338	2.856	-0.118	0.906	-5.936	5.259
[VAR00001 = 1] * [VAR00003 = 0] * [VAR00004 = 1]		0b	.	.	.	.	.
[VAR00001 = 1] * [VAR00003 = 1] * [VAR00004 = 0]		0b	.	.	.	.	.
[VAR00001 = 1] * [VAR00003 = 1] * [VAR00004 = 1]		0b	.	.	.	.	.
[VAR00001 = 2] * [VAR00003 = 0] * [VAR00004 = 0]		-1.863	2.278	-0.818	0.413	-6.327	2.601
[VAR00001 = 2] * [VAR00003 = 0] * [VAR00004 = 1]		0b	.	.	.	.	.
[VAR00001 = 2] * [VAR00003 = 1] * [VAR00004 = 0]		0b	.	.	.	.	.
[VAR00001 = 2] * [VAR00003 = 1] * [VAR00004 = 1]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00003 = 0] * [VAR00004 = 0]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00003 = 0] * [VAR00004 = 1]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00003 = 1] * [VAR00004 = 0]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00003 = 1] * [VAR00004 = 1]		0b	.	.	.	.	.
[VAR00001 = 1] * [VAR00003 = 0] * [VAR00005 = 0]		0.167	3.48	0.048	0.962	-6.654	6.988
[VAR00001 = 1] * [VAR00003 = 0] * [VAR00005 = 1]		0b	.	.	.	.	.
[VAR00001 = 1] * [VAR00003 = 1] * [VAR00005 = 0]		0b	.	.	.	.	.
[VAR00001 = 1] * [VAR00003 = 1] * [VAR00005 = 1]		0b	.	.	.	.	.
[VAR00001 = 2] * [VAR00003 = 0] * [VAR00005 = 0]		0.334	2.906	0.115	0.908	-5.362	6.031
[VAR00001 = 2] * [VAR00003 = 0] * [VAR00005 = 1]		0b	.	.	.	.	.
[VAR00001 = 2] * [VAR00003 = 1] * [VAR00005 = 0]		0b	.	.	.	.	.
[VAR00001 = 2] * [VAR00003 = 1] * [VAR00005 = 1]		0b	.	.	.	.	.
[VAR00001 = 3] * [VAR00003 = 0] * [VAR00005 = 0]		0b	.	.	.	.	.
a. 在多项式假设中常量不作为参数使用。因此不计算它们的标准误差。
b. 此参数为冗余参数，因此将被设为零。
c. 模型：多项 Logit
d. 设计:常量 + VAR00001 + VAR00001 * VAR00002 + VAR00001 * VAR00003 + VAR00001 * VAR00004 + VAR00001 * VAR00005 + VAR00001 * VAR00002 * VAR00003 + VAR00001 * VAR00002 * VAR00004 + VAR00001 * VAR00002 * VAR00005 + VAR00001 * VAR00003 * VAR00004 + VAR00001 * VAR00003 * VAR00005 + VAR00001 * VAR00004 * VAR00005 + VAR00001 * VAR00002 * VAR00003 * VAR00004 + VAR00001 * VAR00002 * VAR00003 * VAR00005 + VAR00001 * VAR00002 * VAR00004 * VAR00005 + VAR00001 * VAR00003 * VAR00004 * VAR00005 + VAR00001 * VAR00002 * VAR00003 * VAR00004 * VAR00005

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关键词：多项Logit模型多项Logit logit模型 logit Log 模型

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沙发

wwlovell 发表于 2011-9-29 18:58:27 |只看作者 |坛友微信交流群

自己顶一下，为啥这个结果显示的和教材上的很不一样啊，尤其是最左一列

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藤椅

huashao214 发表于 2011-9-29 19:47:55 |只看作者 |坛友微信交流群

楼主想问那一部分？
具体点被人才能解答

1

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板凳

wwlovell 发表于 2011-9-29 21:45:27 |只看作者 |坛友微信交流群

怎么没有人解答啊自己顶顶

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报纸

wwlovell 发表于 2011-9-29 22:07:37 |只看作者 |坛友微信交流群

我想问那一列系数是什么意思有什么用谢谢回复

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地板

wwlovell 发表于 2011-9-29 22:09:13 |只看作者 |坛友微信交流群

怎么通过这个算出因变量不同选择的概率

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7楼

猫咪海盗船长 发表于 2011-10-3 21:35:51 |只看作者 |坛友微信交流群

不懂，我也在愁多分类logistic，哪位高手给解答一下

hi！

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