有序多分类重复测量资料的广义线性混合效应模型分析

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1、14中国医院统计2012年2月第19卷第1期有序多分类重复测量资料的广义线性混合效应模型分析张莉娜"摘要#目的探讨广义线性混合效应模型在有序多分类重复测量资料分析中的应用及SAS9.1的GLIMMIX和NLMIXED过程实现O方法为了评价某新药治疗糖尿病神经病变的临床疗效采用以安慰剂为对照的随机双盲临床试验O在各个随访时间记录各受试者的神经病变主觉症状总分并根据减分率评定疗效O建立广义线性混合效应模型并分别用线性化法和数值法积分近似法进行参数估计利用SAS中的GLIMMIX和NLMIXED过程得以实现O结果2种参数估计方法结果很接近O疗效的组间差别有统计学意义P<0.

2、0001试验组疗效优于安慰剂组各个疗程间的疗效差别有统计学意义P<0.0001且疗程越大疗效越好治疗前神经病变主觉症状总分对疗效有影响P:0.0613接近显著性水平其值越高越容易治愈提示病惰严重的患者相比病惰轻微的患者治愈效果更好O另外用数值法积分近似法还给出了随机截距和随机斜率的统计显著性检验O结论采用广义线性混合效应模型对有序多分类重复测量临床资料进行统计分析可以更客观的进行药物疗效评价O"关键词#广义线性混合效应模型重复测量有序多分类GLIMMIXNLMIXEDGeneralizedlinearmixedmodelsfororderedcategorydataw

3、ithrepeatedmeasurementsZHANGli-na.Departmentofbi-ostatistics,ShanghaiiaoTongUniuersity,Schoolofmedicine,Shanghai200025,ChinaAbstractIObjectivetodiscussgeneraiizediinearmixedmodeis(GLMMS>oforderedcategoricairepeatedmeasure-mentdata,andtoimpiementwithGLIMMIXcommandandNLMIXEDcommandinSAS9.

4、1soft.MethodsInordertoassesstheeffectivenessofanewdrugfordiabeticneuropathy,thestudyadoptedrandomized,doubie-biind,piacebo-controiiedciinicaimethod.Ineachfoiiow-uptime,eachpatientfsneuropathysymptomscorewasrecordedandthecurativeeffectwasevaiuatedbyscorereducingrate.wefittedparametermode

5、iappiyingthetheoryofgeneraiizediinearmixedmodeis,andcarriedoutthepa-rameterestimationsusingbothiinearizationmethodandintegraiapproximationwithnumericaimethodbyGLIMMIXandNLMIXEDprocedureinSASsoft.Resultstwokindsofparameterestimationmethodswereveryciosetotheresuits.thediffer-encebetweengr

6、oupswasstatisticaiiysignificant(P<0.0001>.thecurativeeffectsofexperimentgroupwerebetterthanthoseofpiacebogroup.theeffectoftimewasstatisticaiiysignificant(P<0.0001>,andtheiongertimeofthetreatmentreguired,thebettertheresuits.theneuropathysymptomscorebeforetreatmenthadasignificantinfiuence

7、oncurativeeffect(P:0.0613,Ciosetotheieveiofsignificance>,andthehigherthevaiue,themoreiikeiytoheai.Itindicatedthatthecurativeeffectonpa-tientsinseriousconditionwasbetterthanthatonpatientsinmiidcondition.therandominterceptandtherandomsiopecoeffi-cientsweretestedforsignificancebyi