11. Cox regression introduction

11. Cox regression introduction -...

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Unformatted text preview: !"#$%&$($ *+,-./"(&0 !"#1.%23 444 562"78 9:++ ;7"<.2$"%3 #= >&$?"78%#7 !&2@&2& -(A7"8?%B C?DED !4F5G *+, 562"78 9:++ !D -(A7"8?% 4HGIFE;JG4FH GF JFK ILMIL554FH NFI JLH5FILE 5;IO4OPQ EPGP F;GQ4HL M.7.2&0 N#21 #= %?. J#R I.82.$$"#7 -#/.0 J#.S(".7% 47%.262.%&#7 J#7T/.7(. 47%.2<&0$ &7/ U36#%?.$"$ G.$%$ LR&160.$V F7. @"7&23 <&2"&@0. F7. (#77W#W$ 0"7.&2 <&2"&@0. F7. X82#W6./Y0"7.&2Z <&2"&@0. F7. $.% #= /W113 <&2"&@0.$ G[# @"7&23 <&2"&@0.$ F7. @"7&23 &7/ #7. (#77W#W$ 0"7.&2 <&2"&@0. 5%2&T./ J#R -#/.0 \9] !4F5G *+, 562"78 9:++ !D -(A7"8?% JFK ILMIL554FH -FELQ !4F5G *+, 562"78 9:++ !D -(A7"8?% \9^ CIFCFIG4FHPQ UP_PIE5 -FELQ !4F5G *+, 562"78 9:++ !D -(A7"8?% \9 LKP-CQL !4F5G *+, 562"78 9:++ !D -(A7"8?% \,: LKP-CQL Proportional Hazards t ! (t) Parallel Log Hazards t log ! (t) !4F5G *+, 562"78 9:++ !D -(A7"8?% \,+ ILQPG4FH5U4C GF 5;IO4OPQ N;HJG4FH !4F5G *+, 562"78 9:++ !D -(A7"8?% \,9 C4JG;IL 0.0 0.4 0.8 Hazard Function t ! (t) 0.0 0.4 0.8 Survival function t S(t) 0.0 0.4 0.8 Density function t f(t) !4F5G *+, 562"78 9:++ !D -(A7"8?% \,, L5G4-PGL5 PHE JFHN4ELHJL 4HGLIOPQ5 !4F5G *+, 562"78 9:++ !D -(A7"8?% \,\ UaCFGUL545 GL5G5 As before, three tests of H : = are possible: 1. Wald test: se ( ) 2. (Partial) Likelihood ratio test 3. Score test: ( logrank test) !4F5G *+, 562"78 9:++ !D -(A7"8?% \,* 4H 5GPGP !4F5G *+, 562"78 9:++ !D -(A7"8?% \,b . sts test treat failure _d: censor analysis time _t: time Log-rank test for equality of survivor functions | Events Events treat | observed expected------+------------------------- 1 | 64 64.50 2 | 64 63.50------+------------------------- Total | 128 128.00 chi2(1) = 0.01 Pr>chi2 = 0.9277 4H 5GPGP !4F5G *+, 562"78 9:++ !D -(A7"8?% \,] . stcox treat failure _d: censor analysis time _t: time Iteration 0: log likelihood = -505.88396 Iteration 1: log likelihood = -505.87987 Iteration 2: log likelihood = -505.87987 Refining estimates: Iteration 0: log likelihood = -505.87987 Cox regression -- Breslow method for ties No. of subjects = 137 Number of obs = 137 No. of failures = 128 Time at risk = 16663 LR chi2(1) = 0.01 Log likelihood = -505.87987 Prob > chi2 = 0.9280------------------------------------------------------------------------------ _t | Haz. Ratio Std. Err. z P>|z| [95% Conf. Interval]-------------+---------------------------------------------------------------- treat | 1.016462 .1836255 0.09 0.928 .7133788 1.448312------------------------------------------------------------------------------ 5LJFHE LKP-CQL !4F5G *+, 562"78 9:++ !D -(A7"8?% \,^ JFHG4H;F;5 Q4HLPI K Proportional Hazards t ! ( t ) exp( " x) 0.5 1.0 1.5 2.0 Parallel Log Hazards t log ! ( t ) exp( " x) 0.5 1.0 1.5 2.0 !4F5G *+, 562"78 9:++ !D -(A7"8?% \, 4H 5GPGP !4F5G *+, 562"78 9:++ !D -(A7"8?% \\: . stcox status failure _d: censor analysis time _t: time Iteration 0: log likelihood = -505.88396 Iteration 1: log likelihood = -485.31167 Iteration 2: log likelihood = -485.07085log likelihood = -485....
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This note was uploaded on 02/09/2012 for the course STAT 513 taught by Professor Barbaramc.knight during the Spring '11 term at University of Washington.

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11. Cox regression introduction -...

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