I have the clinical study data. Year 0 Year 3 Retinol (nmol/L) N Mean +-sd Mean +-sd Vitamin A group 73 1.89+-0.36 2.06+-0.53 Trace group 57 1.83+-0.31 1.78+-0.30 where N is the number of male for the clinical study. I want to test if the mean serum retinol has increased over 3 years among subjects in the vitamin A group.> 1.89+0.36[1] 2.25> 1.89-0.36[1] 1.53> 2.06+0.53[1] 2.59> 2.06-0.53[1] 1.53> prop.trend.test(c(2.25, 1.53),c( 2.59, 1.53))Chi-squared Test for Trend in Proportions data: c(2.25, 1.53) out of c(2.59, 1.53) , using scores: 1 2 X-squared = 0.2189, df = 1, p-value = 0.6399 The issue I am seeing that N of Vitamin A group = 73 seems not reflected. This leads me to think that I can't implement the test based on the data just presented. Nor a two-tailed test is possible. 2-sample test for equality of proportions with continuity correction data: c(2.25, 1.53) out of c(2.59, 1.53) X-squared = 0, df = 1, p-value = 1 alternative hypothesis: two.sided 95 percent confidence interval: -0.6738203 0.4112720 sample estimates: prop 1 prop 2 0.8687259 1.0000000 Warning message: Chi-squared approximation may be incorrect in: prop.test(c(2.25, 1.53), c(2.59, 1.53)) Any ideas, please? thx ej
At 05:55 03/12/2006, Ethan Johnsons wrote:>I have the clinical study data. > > Year 0 Year 3 >Retinol (nmol/L) N Mean +-sd Mean +-sd >Vitamin A group 73 1.89+-0.36 2.06+-0.53 >Trace group 57 1.83+-0.31 1.78+-0.30 > >where N is the number of male for the clinical study. > >I want to test if the mean serum retinol has increased over 3 years >among subjects in the vitamin A group.If you want to test means why did you think a test for proportions was a good idea?>> 1.89+0.36 >[1] 2.25 >>1.89-0.36 >[1] 1.53 >>2.06+0.53 >[1] 2.59 >>2.06-0.53 >[1] 1.53 > > >>prop.trend.test(c(2.25, 1.53),c( 2.59, 1.53)) > > Chi-squared Test for Trend in Proportions > >data: c(2.25, 1.53) out of c(2.59, 1.53) , >using scores: 1 2 >X-squared = 0.2189, df = 1, p-value = 0.6399 > >The issue I am seeing that N of Vitamin A group = 73 seems not reflected. >This leads me to think that I can't implement the test based on the >data just presented. >Nor a two-tailed test is possible. > > 2-sample test for equality of proportions with continuity correction > >data: c(2.25, 1.53) out of c(2.59, 1.53) >X-squared = 0, df = 1, p-value = 1 >alternative hypothesis: two.sided >95 percent confidence interval: >-0.6738203 0.4112720 >sample estimates: > prop 1 prop 2 >0.8687259 1.0000000 > >Warning message: >Chi-squared approximation may be incorrect in: prop.test(c(2.25, >1.53), c(2.59, 1.53)) > >Any ideas, please? > >thx > >ej > >Michael Dewey http://www.aghmed.fsnet.co.uk
Michael Dewey wrote:> At 13:46 03/12/2006, Ethan Johnsons wrote: > > >I don't find any other test avail for this? > >Am I missing something? > > I do not want to seem unhelpful but the only response that springs to > mind is a knowledge of statistics. > > I hope people's lives are not at stake with the results of your analysisAmen, brother. Well said. Another response springs to *my* mind but it is just as well to suppress it. cheers, Rolf Turner
At 03:55 AM 12/3/2006, Ethan Johnsons wrote:>I have the clinical study data. > > Year 0 Year 3 >Retinol (nmol/L) N Mean +-sd Mean +-sd >Vitamin A group 73 1.89+-0.36 2.06+-0.53 >Trace group 57 1.83+-0.31 1.78+-0.30 > >where N is the number of male for the clinical study. > >I want to test if the mean serum retinol has increased over 3 years >among subjects in the vitamin A group.If You desire check mean serum retinol has increased over 3 years in vitamin A group. You may use t.test Look this example: #Generate random Data set.seed(123) VitA1<-rnorm(73,1.89,.36) Trace1<-rnorm(57,1.83,0.31) VitA2<-rnorm(73,2.06,.53) Trace2<-rnorm(57,1.78,0.30) # Calculate diference Year 3 - Year 0 dVitA<-VitA2-VitA1 dTrace<-Trace2-Trace1 # Testing diference t.test(dVitA,dTrace) Welch Two Sample t-test data: dVitA and dTrace t = 2.2762, df = 117.746, p-value = 0.02464 alternative hypothesis: true difference in means is not equal to 0 95 percent confidence interval: 0.02756874 0.39659494 sample estimates: mean of x mean of y 0.15905162 -0.05303022 Bernardo Rangel Tura, MD, Phd National Institute of Cardiology Laranjeiras Rio de Janeiro Brazil
On 12/4/06, Bernardo Rangel tura <tura at centroin.com.br> wrote:> At 03:55 AM 12/3/2006, Ethan Johnsons wrote: > >I have the clinical study data. > > > > Year 0 Year 3 > >Retinol (nmol/L) N Mean +-sd Mean +-sd > >Vitamin A group 73 1.89+-0.36 2.06+-0.53 > >Trace group 57 1.83+-0.31 1.78+-0.30 > > > >where N is the number of male for the clinical study. > > > >I want to test if the mean serum retinol has increased over 3 years > >among subjects in the vitamin A group. > > > If You desire check mean serum retinol has increased over 3 years in > vitamin A group. > You may use t.test > Look this example: > > #Generate random Data > > set.seed(123) > VitA1<-rnorm(73,1.89,.36) > Trace1<-rnorm(57,1.83,0.31) > VitA2<-rnorm(73,2.06,.53) > Trace2<-rnorm(57,1.78,0.30) > > # Calculate diference Year 3 - Year 0 > > dVitA<-VitA2-VitA1 > dTrace<-Trace2-Trace1 > > # Testing diference > t.test(dVitA,dTrace) > > > Welch Two Sample t-test > > data: dVitA and dTrace > t = 2.2762, df = 117.746, p-value = 0.02464 > alternative hypothesis: true difference in means is not equal to 0 > 95 percent confidence interval: > 0.02756874 0.39659494 > sample estimates: > mean of x mean of y > 0.15905162 -0.05303022 > > > > > > Bernardo Rangel Tura, MD, Phd > National Institute of Cardiology Laranjeiras > Rio de Janeiro Brazil > >Thank you so much. It is clear now. ej