公开(公告)号：US20110082827A1

公开(公告)日：2011-04-07

申请号：US12965719

申请日：2010-12-10

申请人： Saul SHIFFMAN ,  Douglas R. Engfer ,  Jean Paty

发明人： Saul SHIFFMAN ,  Douglas R. Engfer ,  Jean Paty

IPC分类号： G06N5/02 ,  G06F17/00

CPC分类号： G06F17/30539 ,  G06F17/30528 ,  G06N5/02 ,  G06N5/025

摘要： A system for developing and implementing empirically derived algorithms to generate decision rules to predict invalidity of subject reported data and fraud with research protocols in surveys allows for the identification of complex patterns of variables that detect or predict subject invalidity of subject reported data and fraud with the research protocol in the survey. The present invention may also be used to monitor invalidity of subject reported data within a research protocol to determine preferred actions to be performed. Optionally, the invention may provide a spectrum of invalidity, from minor invalidity needing only corrective feedback, to significant invalidity requiring subject removal from the survey. The algorithms and decision rules can also be domain-specific, such as detecting invalidity or fraud among subjects in a workplace satisfaction survey, or demographically specific, such as taking into account gender or age. The algorithms and decision rules may be optimized for the specific sample of subjects being studied.

摘要翻译： 用于开发和实施经验导出的算法以生成决策规则以通过调查研究方案预测受试者报告数据和欺诈的无效性的系统允许识别检测或预测主题报告数据和欺诈的主体无效的变量的复杂模式 研究方案在调查中。 本发明还可用于监测研究协议内被检体报告数据的无效性，以确定要执行的优选动作。 任选地，本发明可以提供一系列无效性，从仅需要校正反馈的轻微无效，到需要从调查中移除问题的显着无效。 算法和决策规则也可以是域特定的，例如在工作场所满意度调查中检测主体之间的无效或欺诈，或者人口特异性，例如考虑到性别或年龄。 可以针对正在研究的受试者的具体样本优化算法和决策规则。

公开(公告)号：US07873589B2

公开(公告)日：2011-01-18

申请号：US11844632

申请日：2007-08-24

申请人： Saul Shiffman ,  Douglas R. Engfer ,  Jean Paty

发明人： Saul Shiffman ,  Douglas R. Engfer ,  Jean Paty

IPC分类号： G06F17/00 ,  G06N5/02

CPC分类号： G06F17/30539 ,  G06F17/30528 ,  G06N5/02 ,  G06N5/025

摘要： A system for developing and implementing empirically derived algorithms to generate decision rules to predict invalidity of subject reported data and fraud with research protocols in surveys allows for the identification of complex patterns of variables that detect or predict subject invalidity of subject reported data and fraud with the research protocol in the survey. The present invention may also be used to monitor invalidity of subject reported data within a research protocol to determine preferred actions to be performed. Optionally, the invention may provide a spectrum of invalidity, from minor invalidity needing only corrective feedback, to significant invalidity requiring subject removal from the survey. The algorithms and decision rules can also be domain-specific, such as detecting invalidity or fraud among subjects in a workplace satisfaction survey, or demographically specific, such as taking into account gender or age. The algorithms and decision rules may be optimized for the specific sample of subjects being studied.

摘要翻译： 用于开发和实施经验导出的算法以生成决策规则以通过调查研究方案预测受试者报告数据和欺诈的无效性的系统允许识别检测或预测主题报告数据和欺诈的主体无效的变量的复杂模式 研究方案在调查中。 本发明还可用于监测研究协议内被检体报告数据的无效性，以确定要执行的优选动作。 任选地，本发明可以提供一系列无效性，从仅需要校正反馈的轻微无效，到需要从调查中移除问题的显着无效。 算法和决策规则也可以是域特定的，例如在工作场所满意度调查中检测主体之间的无效或欺诈，或者人口特异性，例如考虑到性别或年龄。 可以针对正在研究的受试者的具体样本优化算法和决策规则。

公开(公告)号：US09129215B2

公开(公告)日：2015-09-08

申请号：US12965719

申请日：2010-12-10

申请人： Saul Shiffman ,  Douglas R. Engfer ,  Jean Paty

发明人： Saul Shiffman ,  Douglas R. Engfer ,  Jean Paty

IPC分类号： G06F1/00 ,  G06N5/00 ,  G06N5/02

CPC分类号： G06F17/30539 ,  G06F17/30528 ,  G06N5/02 ,  G06N5/025

摘要： A system for developing and implementing empirically derived algorithms to generate decision rules to predict invalidity of subject reported data and fraud with research protocols in surveys allows for the identification of complex patterns of variables that detect or predict subject invalidity of subject reported data and fraud with the research protocol in the survey. The present invention may also be used to monitor invalidity of subject reported data within a research protocol to determine preferred actions to be performed. Optionally, the invention may provide a spectrum of invalidity, from minor invalidity needing only corrective feedback, to significant invalidity requiring subject removal from the survey. The algorithms and decision rules can also be domain-specific, such as detecting invalidity or fraud among subjects in a workplace satisfaction survey, or demographically specific, such as taking into account gender or age. The algorithms and decision rules may be optimized for the specific sample of subjects being studied.

摘要翻译： 用于开发和实施经验导出的算法以生成决策规则以通过调查研究方案预测受试者报告数据和欺诈的无效性的系统允许识别检测或预测主题报告数据和欺诈的主体无效的变量的复杂模式 研究方案在调查中。 本发明还可用于监测研究协议内被检体报告数据的无效性，以确定要执行的优选动作。 任选地，本发明可以提供一系列无效性，从仅需要校正反馈的轻微无效，到需要从调查中移除问题的显着无效。 算法和决策规则也可以是域特定的，例如在工作场所满意度调查中检测主体之间的无效或欺诈，或者人口特异性，例如考虑到性别或年龄。 可以针对正在研究的受试者的具体样本优化算法和决策规则。