) 北京师范大学中国基础教育质量监测协同创新中心, 北京 100875
收稿日期:2018-06-07出版日期:2019-05-15发布日期:2019-03-20通讯作者:陈平E-mail:pchen@bnu.edu.cn基金资助:* 国家自然科学基金青年基金项目(31300862);东北师范大学应用统计教育部重点实验室开放课题(KLAS130028732);中国基础教育质量监测协同创新中心研究生自主课题资助(BJSM-2016A1-16004)Explanatory item response theory models: Theory and application
CHEN Guanyu, CHEN Ping() Collaborative Innovation Center of Assessment toward Basic Education Quality, Beijing Normal University, Beijing 100875, China
Received:2018-06-07Online:2019-05-15Published:2019-03-20Contact:CHEN Ping E-mail:pchen@bnu.edu.cn摘要/Abstract
摘要： 解释性项目反应理论模型(Explanatory Item Response Theory Models, EIRTM)是指基于广义线性混合模型和非线性混合模型构建的项目反应理论(Item Response Theory, IRT)模型。EIRTM能在IRT模型的基础上直接加入预测变量, 从而解决各类测量问题。首先介绍EIRTM的相关概念和参数估计方法, 然后展示如何使用EIRTM处理题目位置效应、测验模式效应、题目功能差异、局部被试依赖和局部题目依赖, 接着提供实例对EIRTM的使用进行说明, 最后对EIRTM的不足之处和应用前景进行讨论。
图/表 3
图1题目、被试和群体的层级关系图 注：图片翻译自Jiao, Kamata和Xie (2015, p. 145) 图5.3
图1题目、被试和群体的层级关系图 注：图片翻译自Jiao, Kamata和Xie (2015, p. 145) 图5.3表124道言语攻击题目
| 题目 | 行为模式 | 情境类型 | 行为类型 |
|---|---|---|---|
| 一辆公交车没有进站停靠, 我想诅咒。 | 想 | 他人责任 | 诅咒 |
| 一辆公交车没有进站停靠, 我想责备。 | 想 | 他人责任 | 责备 |
| 一辆公交车没有进站停靠, 我想怒骂。 | 想 | 他人责任 | 怒骂 |
| 因为工作人员给我错误的信息, 我错过了火车, 我想诅咒。 | 想 | 他人责任 | 诅咒 |
| 因为工作人员给我错误的信息, 我错过了火车, 我想责备。 | 想 | 他人责任 | 责备 |
| 因为工作人员给我错误的信息, 我错过了火车, 我想怒骂。 | 想 | 他人责任 | 怒骂 |
| 当我刚进入商店, 商店就关门了, 我想诅咒。 | 想 | 自己责任 | 诅咒 |
| 当我刚进入商店, 商店就关门了, 我想责备。 | 想 | 自己责任 | 责备 |
| 当我刚进入商店, 商店就关门了, 我想怒骂。 | 想 | 自己责任 | 怒骂 |
| 我与对方的通话断了, 因为我用完了话费, 我想诅咒。 | 想 | 自己责任 | 诅咒 |
| 我与对方的通话断了, 因为我用完了话费, 我想责备。 | 想 | 自己责任 | 责备 |
| 我与对方的通话断了, 因为我用完了话费, 我想怒骂。 | 想 | 自己责任 | 怒骂 |
| 一辆公交车没有进站停靠, 我会诅咒。 | 做 | 他人责任 | 诅咒 |
| 一辆公交车没有进站停靠, 我会责备。 | 做 | 他人责任 | 责备 |
| 一辆公交车没有进站停靠, 我会怒骂。 | 做 | 他人责任 | 怒骂 |
| 因为工作人员给我错误的信息, 我错过了火车, 我会诅咒。 | 做 | 他人责任 | 诅咒 |
| 因为工作人员给我错误的信息, 我错过了火车, 我会责备。 | 做 | 他人责任 | 责备 |
| 因为工作人员给我错误的信息, 我错过了火车, 我会怒骂。 | 做 | 他人责任 | 怒骂 |
| 当我刚进入商店, 商店就关门了, 我会诅咒。 | 做 | 自己责任 | 诅咒 |
| 当我刚进入商店, 商店就关门了, 我会责备。 | 做 | 自己责任 | 责备 |
| 当我刚进入商店, 商店就关门了, 我会怒骂。 | 做 | 自己责任 | 怒骂 |
| 我与对方的通话断了, 因为我用完了话费, 我会诅咒。 | 做 | 自己责任 | 诅咒 |
| 我与对方的通话断了, 因为我用完了话费, 我会责备。 | 做 | 自己责任 | 责备 |
| 我与对方的通话断了, 因为我用完了话费, 我会怒骂。 | 做 | 自己责任 | 怒骂 |
表124道言语攻击题目
| 题目 | 行为模式 | 情境类型 | 行为类型 |
|---|---|---|---|
| 一辆公交车没有进站停靠, 我想诅咒。 | 想 | 他人责任 | 诅咒 |
| 一辆公交车没有进站停靠, 我想责备。 | 想 | 他人责任 | 责备 |
| 一辆公交车没有进站停靠, 我想怒骂。 | 想 | 他人责任 | 怒骂 |
| 因为工作人员给我错误的信息, 我错过了火车, 我想诅咒。 | 想 | 他人责任 | 诅咒 |
| 因为工作人员给我错误的信息, 我错过了火车, 我想责备。 | 想 | 他人责任 | 责备 |
| 因为工作人员给我错误的信息, 我错过了火车, 我想怒骂。 | 想 | 他人责任 | 怒骂 |
| 当我刚进入商店, 商店就关门了, 我想诅咒。 | 想 | 自己责任 | 诅咒 |
| 当我刚进入商店, 商店就关门了, 我想责备。 | 想 | 自己责任 | 责备 |
| 当我刚进入商店, 商店就关门了, 我想怒骂。 | 想 | 自己责任 | 怒骂 |
| 我与对方的通话断了, 因为我用完了话费, 我想诅咒。 | 想 | 自己责任 | 诅咒 |
| 我与对方的通话断了, 因为我用完了话费, 我想责备。 | 想 | 自己责任 | 责备 |
| 我与对方的通话断了, 因为我用完了话费, 我想怒骂。 | 想 | 自己责任 | 怒骂 |
| 一辆公交车没有进站停靠, 我会诅咒。 | 做 | 他人责任 | 诅咒 |
| 一辆公交车没有进站停靠, 我会责备。 | 做 | 他人责任 | 责备 |
| 一辆公交车没有进站停靠, 我会怒骂。 | 做 | 他人责任 | 怒骂 |
| 因为工作人员给我错误的信息, 我错过了火车, 我会诅咒。 | 做 | 他人责任 | 诅咒 |
| 因为工作人员给我错误的信息, 我错过了火车, 我会责备。 | 做 | 他人责任 | 责备 |
| 因为工作人员给我错误的信息, 我错过了火车, 我会怒骂。 | 做 | 他人责任 | 怒骂 |
| 当我刚进入商店, 商店就关门了, 我会诅咒。 | 做 | 自己责任 | 诅咒 |
| 当我刚进入商店, 商店就关门了, 我会责备。 | 做 | 自己责任 | 责备 |
| 当我刚进入商店, 商店就关门了, 我会怒骂。 | 做 | 自己责任 | 怒骂 |
| 我与对方的通话断了, 因为我用完了话费, 我会诅咒。 | 做 | 自己责任 | 诅咒 |
| 我与对方的通话断了, 因为我用完了话费, 我会责备。 | 做 | 自己责任 | 责备 |
| 我与对方的通话断了, 因为我用完了话费, 我会怒骂。 | 做 | 自己责任 | 怒骂 |
表224道言语攻击题目的固定效应
| 题目 | 模型1 | 模型2 | 模型3 | 模型4 | |||
|---|---|---|---|---|---|---|---|
| βq | βq | 行为模式 | βq | DIF | 95%置信区间 | βq | |
| 1 | -1.162 | -1.148 | -1.196 | -0.101 | (-0.723, 0.549) | -1.248 | |
| 2 | -0.546 | -0.531 | -0.574 | -0.104 | (-0.717, 0.505) | -0.584 | |
| 3 | -0.091 | -0.074 | -0.134 | -0.171 | (-0.777, 0.431) | -0.101 | |
| 4 | -1.657 | -1.641 | -1.727 | -0.261 | (-0.934, 0.449) | -1.800 | |
| 5 | -0.681 | -0.667 | -0.729 | -0.182 | (-0.800, 0.433) | -0.746 | |
| 6 | -0.026 | -0.011 | -0.184 | -0.684 | (-1.293, -0.070) | -0.031 | |
| 7 | -0.512 | -0.496 | -0.495 | 0.103 | (-0.507, 0.721) | -0.617 | |
| 8 | 0.630 | 0.643 | 0.751 | 0.535 | (-0.067, 1.151) | 0.689 | |
| 9 | 1.430 | 1.451 | 1.338 | -0.455 | (-1.153, 0.240) | 1.610 | |
| 10 | -1.014 | -0.998 | -1.071 | -0.221 | (-0.853, 0.415) | -1.221 | |
| 11 | 0.312 | 0.329 | 0.362 | 0.231 | (-0.376, 0.826) | 0.354 | |
| 12 | 0.963 | 0.982 | 0.866 | -0.454 | (-1.104, 0.185) | 1.132 | |
| 13 | -1.145 | -1.580 | -0.465 | -1.066 | 0.426 | (-0.251, 1.108) | -1.225 |
| 14 | -0.383 | -0.820 | -0.465 | -0.215 | 0.792 | (0.156, 1.420) | -0.412 |
| 15 | 0.820 | 0.381 | -0.465 | 0.786 | -0.133 | (-0.767, 0.487) | 0.885 |
| 16 | -0.822 | -1.260 | -0.465 | -0.618 | 1.006 | (0.352, 1.706) | -0.895 |
| 17 | 0.035 | -0.404 | -0.465 | 0.263 | 1.019 | (0.409, 1.648) | 0.042 |
| 18 | 1.372 | 0.933 | -0.465 | 1.422 | 0.222 | (-0.417, 0.879) | 1.498 |
| 19 | 0.200 | -0.240 | -0.465 | 0.393 | 0.864 | (0.280, 1.481) | 0.199 |
| 20 | 1.390 | 0.956 | -0.465 | 1.579 | 0.750 | (0.093, 1.390) | 1.563 |
| 21 | 2.711 | 2.277 | -0.465 | 2.775 | 0.244 | (-0.615, 1.062) | 3.034 |
| 22 | -0.660 | -1.106 | -0.465 | -0.548 | 0.568 | (-0.068, 1.205) | -0.801 |
| 23 | 0.363 | -0.080 | -0.465 | 0.488 | 0.546 | (-0.059, 1.146) | 0.416 |
| 24 | 1.867 | 1.427 | -0.465 | 1.799 | -0.359 | (-1.138, 0.375) | 2.202 |
表224道言语攻击题目的固定效应
| 题目 | 模型1 | 模型2 | 模型3 | 模型4 | |||
|---|---|---|---|---|---|---|---|
| βq | βq | 行为模式 | βq | DIF | 95%置信区间 | βq | |
| 1 | -1.162 | -1.148 | -1.196 | -0.101 | (-0.723, 0.549) | -1.248 | |
| 2 | -0.546 | -0.531 | -0.574 | -0.104 | (-0.717, 0.505) | -0.584 | |
| 3 | -0.091 | -0.074 | -0.134 | -0.171 | (-0.777, 0.431) | -0.101 | |
| 4 | -1.657 | -1.641 | -1.727 | -0.261 | (-0.934, 0.449) | -1.800 | |
| 5 | -0.681 | -0.667 | -0.729 | -0.182 | (-0.800, 0.433) | -0.746 | |
| 6 | -0.026 | -0.011 | -0.184 | -0.684 | (-1.293, -0.070) | -0.031 | |
| 7 | -0.512 | -0.496 | -0.495 | 0.103 | (-0.507, 0.721) | -0.617 | |
| 8 | 0.630 | 0.643 | 0.751 | 0.535 | (-0.067, 1.151) | 0.689 | |
| 9 | 1.430 | 1.451 | 1.338 | -0.455 | (-1.153, 0.240) | 1.610 | |
| 10 | -1.014 | -0.998 | -1.071 | -0.221 | (-0.853, 0.415) | -1.221 | |
| 11 | 0.312 | 0.329 | 0.362 | 0.231 | (-0.376, 0.826) | 0.354 | |
| 12 | 0.963 | 0.982 | 0.866 | -0.454 | (-1.104, 0.185) | 1.132 | |
| 13 | -1.145 | -1.580 | -0.465 | -1.066 | 0.426 | (-0.251, 1.108) | -1.225 |
| 14 | -0.383 | -0.820 | -0.465 | -0.215 | 0.792 | (0.156, 1.420) | -0.412 |
| 15 | 0.820 | 0.381 | -0.465 | 0.786 | -0.133 | (-0.767, 0.487) | 0.885 |
| 16 | -0.822 | -1.260 | -0.465 | -0.618 | 1.006 | (0.352, 1.706) | -0.895 |
| 17 | 0.035 | -0.404 | -0.465 | 0.263 | 1.019 | (0.409, 1.648) | 0.042 |
| 18 | 1.372 | 0.933 | -0.465 | 1.422 | 0.222 | (-0.417, 0.879) | 1.498 |
| 19 | 0.200 | -0.240 | -0.465 | 0.393 | 0.864 | (0.280, 1.481) | 0.199 |
| 20 | 1.390 | 0.956 | -0.465 | 1.579 | 0.750 | (0.093, 1.390) | 1.563 |
| 21 | 2.711 | 2.277 | -0.465 | 2.775 | 0.244 | (-0.615, 1.062) | 3.034 |
| 22 | -0.660 | -1.106 | -0.465 | -0.548 | 0.568 | (-0.068, 1.205) | -0.801 |
| 23 | 0.363 | -0.080 | -0.465 | 0.488 | 0.546 | (-0.059, 1.146) | 0.416 |
| 24 | 1.867 | 1.427 | -0.465 | 1.799 | -0.359 | (-1.138, 0.375) | 2.202 |
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