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标题: 两因素中简单效应分析怎么做 [打印本页]

作者: 垂耳兔 时间: 2013-3-13 22:58
标题: 两因素中简单效应分析怎么做
两因素方差分析以后，想在F1这个因素的四个水平上对F2得到的数据进行两两比较，虽然查了些资料，但是还是不知道该怎样做这个简单效应分析，我自己试了试，还是没弄明白，连结果都看不懂......数据就列在下面了，请各位高手帮忙指点一下，在SPSS中应该如何做？结果应该怎样看？如果能够帮忙把结果做出来那更是不胜感激。
F1 F2 N
1.0 1.0 -6.0
1.0 1.0 0.7781512503836436
1.0 1.0 0.6989700043360189
1.0 1.0 -3.0
1.0 1.0 -3.0
1.0 1.0 -6.0
1.0 1.0 -6.0
1.0 1.0 -6.0
1.0 1.0 -6.0
1.0 2.0 1.0791812460476249
1.0 2.0 1.1760912590556813
1.0 2.0 1.146128035678238
1.0 2.0 0.0
1.0 2.0 0.3010299956639812
1.0 2.0 0.0
1.0 2.0 0.0
1.0 2.0 -6.0
1.0 2.0 -6.0
1.0 3.0 -6.0
1.0 3.0 -6.0
1.0 3.0 -6.0
1.0 3.0 -6.0
1.0 3.0 -6.0
1.0 3.0 -6.0
1.0 3.0 -6.0
1.0 3.0 -6.0
1.0 3.0 -6.0
1.0 4.0 2.0
1.0 4.0 1.7781512503836436
1.0 4.0 1.954242509439325
1.0 4.0 1.4771212547196624
1.0 4.0 1.0
1.0 4.0 1.0
1.0 4.0 -6.0
1.0 4.0 -6.0
1.0 4.0 -6.0
1.0 5.0 1.9030899869919435
1.0 5.0 1.0
1.0 5.0 -6.0
1.0 5.0 1.3010299956639813
1.0 5.0 -6.0
1.0 5.0 -6.0
1.0 5.0 1.0
1.0 5.0 1.954242509439325
1.0 5.0 1.3010299956639813
1.0 6.0 2.113943352306837
1.0 6.0 2.113943352306837
1.0 6.0 1.3424226808222062
1.0 6.0 1.0413926851582251
1.0 6.0 2.0
1.0 6.0 1.954242509439325
1.0 6.0 2.2041199826559246
1.0 6.0 2.0791812460476247
1.0 6.0 2.1760912590556813
2.0 1.0 5.0
2.0 1.0 5.0
2.0 1.0 5.0
2.0 1.0 -6.0
2.0 1.0 -6.0
2.0 1.0 -6.0
2.0 1.0 -6.0
2.0 1.0 -6.0
2.0 1.0 -6.0
2.0 2.0 6.477121254719663
2.0 2.0 6.778151250383644
2.0 2.0 6.0
2.0 2.0 6.0
2.0 2.0 6.477121254719663
2.0 2.0 -6.0
2.0 2.0 -6.0
2.0 2.0 -6.0
2.0 2.0 -6.0
2.0 3.0 8.372912002970107
2.0 3.0 8.307496037913213
2.0 3.0 8.301029995663981
2.0 3.0 8.369215857410143
2.0 3.0 8.344392273685111
2.0 3.0 8.401400540781545
2.0 3.0 8.324282455297693
2.0 3.0 8.320146286111054
2.0 3.0 8.340444114840118
2.0 4.0 6.954242509439325
2.0 4.0 7.380211241711606
2.0 4.0 6.845098040014257
2.0 4.0 7.113943352306837
2.0 4.0 6.903089986991944
2.0 4.0 7.079181246047625
2.0 4.0 6.954242509439325
2.0 4.0 6.778151250383644
2.0 4.0 7.041392685158225
2.0 5.0 8.540329474790873
2.0 5.0 8.56702636615906
2.0 5.0 8.593286067020458
2.0 5.0 8.571708831808687
2.0 5.0 8.506505032404872
2.0 5.0 8.558708570533165
2.0 5.0 8.547774705387823
2.0 5.0 8.489958479424836
2.0 5.0 8.58206336291171
2.0 6.0 8.625312450961674
2.0 6.0 8.640481436970422
2.0 6.0 8.61066016308988
2.0 6.0 8.614897216033135
2.0 6.0 8.636487896353366
2.0 6.0 8.602059991327963
3.0 1.0 4.146128035678238
3.0 1.0 4.041392685158225
3.0 1.0 4.698970004336019
3.0 1.0 4.342422680822207
3.0 1.0 4.301029995663981
3.0 1.0 4.447158031342219
3.0 1.0 4.477121254719663
3.0 1.0 4.6127838567197355
3.0 1.0 4.643452676486188
3.0 2.0 3.7781512503836434
3.0 2.0 3.6020599913279625
3.0 2.0 3.4771212547196626
3.0 2.0 -6.0
3.0 2.0 3.0
3.0 2.0 3.6020599913279625
3.0 2.0 3.3010299956639813
3.0 2.0 -6.0
3.0 2.0 -6.0
3.0 3.0 5.477121254719663
3.0 3.0 5.477121254719663
3.0 3.0 6.113943352306837
3.0 3.0 5.6020599913279625
3.0 3.0 5.477121254719663
3.0 3.0 5.0
3.0 3.0 5.301029995663981
3.0 3.0 -6.0
3.0 3.0 -6.0
3.0 4.0 7.238046103128795
3.0 4.0 7.146128035678238
3.0 4.0 7.209515014542631
3.0 4.0 7.133538908370218
3.0 4.0 7.278753600952829
3.0 4.0 7.267171728403014
3.0 4.0 7.269512944217916
3.0 4.0 7.123851640967086
3.0 4.0 7.209515014542631
3.0 5.0 6.3222192947339195
3.0 5.0 6.361727836017593
3.0 5.0 6.2552725051033065
3.0 5.0 6.414973347970818
3.0 5.0 6.278753600952829
3.0 5.0 6.342422680822207
3.0 5.0 6.380211241711606
3.0 5.0 6.204119982655925
3.0 5.0 6.3979400086720375
3.0 6.0 8.212187604403958
3.0 6.0 8.02530586526477
3.0 6.0 8.089905111439398
3.0 6.0 8.198657086954423
3.0 6.0 8.227886704613674
4.0 1.0 4.008600171761918
4.0 1.0 4.232996110392154
4.0 1.0 3.9590413923210934
4.0 1.0 4.136720567156407
4.0 1.0 4.195899652409234
4.0 1.0 4.02530586526477
4.0 1.0 4.431363764158987
4.0 1.0 4.589949601325708
4.0 1.0 4.608526033577194
4.0 2.0 2.0
4.0 2.0 2.0
4.0 2.0 -6.0
4.0 2.0 2.4771212547196626
4.0 2.0 2.3010299956639813
4.0 2.0 2.3010299956639813
4.0 2.0 3.041392685158225
4.0 2.0 2.3010299956639813
4.0 2.0 2.3010299956639813
4.0 3.0 -6.0
4.0 3.0 -6.0
4.0 3.0 3.0
4.0 3.0 -6.0
4.0 3.0 -6.0
4.0 3.0 3.0
4.0 3.0 3.6989700043360187
4.0 3.0 3.3010299956639813
4.0 3.0 -6.0
4.0 4.0 -6.0
4.0 4.0 -6.0
4.0 4.0 3.3010299956639813
4.0 4.0 3.0
4.0 4.0 3.3010299956639813
4.0 4.0 -6.0
4.0 4.0 3.0
4.0 4.0 3.3010299956639813
4.0 4.0 3.0
4.0 5.0 3.6020599913279625
4.0 5.0 3.4771212547196626
4.0 5.0 3.6020599913279625
4.0 5.0 3.3010299956639813
4.0 5.0 3.7781512503836434
4.0 5.0 3.845098040014257
4.0 5.0 4.361727836017593
4.0 5.0 4.491361693834273
4.0 5.0 4.278753600952829
4.0 6.0 -6.0
4.0 6.0 5.0
4.0 6.0 5.301029995663981
4.0 6.0 -6.0
4.0 6.0 5.0

作者: abc886y365hxg 时间: 2013-3-14 09:23
上excel表，没有谁会慢慢给你输入的计算给你看的

作者: 垂耳兔 时间: 2013-3-14 11:32
不好意思，考虑的不周全了，现在把excel表传上来

分析数据.xls (27 KB, 下载次数: 1029)

作者: shouyi123 时间: 2013-5-23 22:40
建议网上搜索简单效应SPSS 程序语句就OK

作者: O(∩_∩)O 时间: 2013-5-24 13:31
晕，过去好长时间了

作者: 小鱼 时间: 2013-5-24 20:24
SAS编程的话比较简单吧
contrast 语句

作者: bingo 时间: 2013-6-2 21:01
你用SPSS的话，可以看丁国盛的spss书籍，或者舒华和张亚旭编著的《心理学研究方法》里面有如何做简单效应检验的。很详细的
而且你的实验设计也不清楚，是被试内设计还是混合设计，都是有差别的。

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