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第1页共9页编号：时间：2021年x月x日书山有路勤为径，学海无涯苦作舟页码：第1页共9页基于GLM（广义线性模型）的数据分析SAS里的GLM应用在实际中比较广泛，对数据的分析具有比较强的普适性。趋势面回归分析（TrendAnalysis）是以多元回归分析为理论基础的一种预测与统计技术。它用空间坐标法进行多项式回归，从中估计出最佳的回归模型，因此也被称为趋势面分析，当不知道手中的数据呈线性还是非线性相关时，可以采用趋势面数据分析方法，以便找出拟合数据的最佳统计预测模型。本文运用GLM对一定的数据进行GLM分析。一、数据与要求此处选取15名吧不同程度的烟民的每日饮酒（啤酒）量与心电图指标（zb）的对应数据。然后设法建立zb与日抽烟量（X）/支和日饮酒量（y）/升之间的关系。序号组别日抽烟量（x）/支日饮酒量（y）/升心电图指标（zb）113010280212511260313513330414014400514514410622012270721811210822512280922513300102231329011340144101234515420133481642514350184501535519470二、运用GLM过程进行趋势面分析1.趋势分析的GLM程序databeer;第2页共9页第1页共9页编号：时间：2021年x月x日书山有路勤为径，学海无涯苦作舟页码：第2页共9页inputobsnxyzb;cards;013010280022511260033513330044014400054514410062012270071811210082512280092513300102313290114014410124515420134816425145018450155519470;procglm;modelzb=xy/p;procglm;modelzb=xyx*xx*yy*y/p;procglm;modelzb=xyx*x*xx*x*yx*y*yy*y*y/p;procglm;modelzb=xyx*x*xx*x*yx*y*yy*y*yx*x*x*xx*x*x*yx*x*y*yx*y*y*yy*y*y*y/p;run;2.四种分析模型结果（1）一阶趋势模型DependentVariable:zb源变量自由度平方和均值F值概率值SumofSourceDFSquaresMeanSquareFValuePr>FModel290615.2099345307.60497127.19<.0001Error124274.79007356.23251CorrectedTotal1494890.00000R-SquareCoeffVarRootMSEzbMean0.9549505.43922818.87412347.000----------------------------------------------------------------------------------------------------------------------第3页共9页第2页共9页编号：时间：2021年x月x日书山有路勤为径，学海无涯苦作舟页码：第3页共9页-----------SourceDFTypeISSMeanSquareFValuePr>Fx189541.5655889541.56558251.36<.0001y11073.644351073.644353.010.1081---------------------------------------------------------------------------------------------------------------------------------SourceDFTypeIIISSMeanSquareFValuePr>Fx114652.2435114652.2435141.13<.0001y11073.644351073.644353.010.1081---------------------------------------------------------------------------------------------------------------------------------StandardParameterEstimateErrortValuePr>|t|Intercept64.0499938033.065399191.940.0766x5.383855650.839475676.41<.0001y6.941998693.998720781.740.1081ObservationObservedPredictedResidual1280.0000000294.9856503-14.98565032260.0000000275.0083707-15.00837073330.0000000342.7309246-12.73092464400.0000000376.592201523.40779855410.0000000403.51147986.48852026270.0000000255.031091114.96890897210.0000000237.3213811-27.32138118280.0000000281.9503694-1.95036949300.0000000288.892368111.107631910290.0000000278.124656811.875343211410.0000000376.592201533.407798512420.0000000410.45347859.546521513425.0000000433.5470441-8.547044114450.0000000458.1987528-8.198752815470.0000000492.0600298-22.0600298---------------------------------------------------------------------------------------------------------------------------------SumofResiduals-0.000000SumofSquaredResiduals4274.790069SumofSquaredResiduals-ErrorSS-0.000000FirstOrderAutocorrelation0.235461Durbin-WatsonD1.362704（2）二阶趋势模型第4页共9页第3页共9页编号：时间：2021年x月x日书山有路勤为径，学海无涯苦作舟页码：第4...