
R version 4.3.1 (2023-06-16) -- "Beagle Scouts"
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> 
> ## examples from Breslow & Chatterjee: Applied Statistics 1999 No. 4, p458
> ## data from Norman Breslow's web page.
> library(survey)
Loading required package: grid
Loading required package: Matrix
Loading required package: survival

Attaching package: 'survey'

The following object is masked from 'package:graphics':

    dotchart

> load("nwts.rda")
> nwtsnb<-nwts
> nwtsnb$case<-nwts$case-nwtsb$case
> nwtsnb$control<-nwts$control-nwtsb$control
> 
> a<-rbind(nwtsb,nwtsnb)
> a$in.ccs<-rep(c(TRUE,FALSE),each=16)
> 
> b<-rbind(a,a)
> b$rel<-rep(c(1,0),each=32)
> b$n<-ifelse(b$rel,b$case,b$control)
> 
> index<-rep(1:64,b$n)
> 
> nwt.exp<-b[index,c(1:3,6,7)]
> nwt.exp$id<-1:4088
> 
> dccs2<-twophase(id=list(~id,~id),subset=~in.ccs,
+                 strata=list(NULL,~interaction(instit,rel)),data=nwt.exp)
> 
> dccs8<-twophase(id=list(~id,~id),subset=~in.ccs,
+                 strata=list(NULL,~interaction(instit,stage,rel)),data=nwt.exp)
> 
> gccs8<-calibrate(dccs2,phase=2,formula=~interaction(instit,stage,rel))
> 
> summary(svyglm(rel~factor(stage)*factor(histol),family=quasibinomial,design=dccs2))

Call:
svyglm(formula = rel ~ factor(stage) * factor(histol), design = dccs2, 
    family = quasibinomial)

Survey design:
twophase(id = list(~id, ~id), subset = ~in.ccs, strata = list(NULL, 
    ~interaction(instit, rel)), data = nwt.exp)

Coefficients:
                               Estimate Std. Error t value Pr(>|t|)    
(Intercept)                     -2.5701     0.1288 -19.955  < 2e-16 ***
factor(stage)2                   0.5482     0.1979   2.769 0.005708 ** 
factor(stage)3                   0.4791     0.2032   2.359 0.018515 *  
factor(stage)4                   1.0037     0.2592   3.872 0.000114 ***
factor(histol)2                  1.3505     0.3107   4.346 1.51e-05 ***
factor(stage)2:factor(histol)2   0.1152     0.4410   0.261 0.793876    
factor(stage)3:factor(histol)2   0.5066     0.4241   1.194 0.232548    
factor(stage)4:factor(histol)2   0.9785     0.6214   1.575 0.115615    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for quasibinomial family taken to be 1.000876)

Number of Fisher Scoring iterations: 4

> summary(svyglm(rel~factor(stage)*factor(histol),family=quasibinomial,design=dccs8))

Call:
svyglm(formula = rel ~ factor(stage) * factor(histol), design = dccs8, 
    family = quasibinomial)

Survey design:
twophase(id = list(~id, ~id), subset = ~in.ccs, strata = list(NULL, 
    ~interaction(instit, stage, rel)), data = nwt.exp)

Coefficients:
                               Estimate Std. Error t value Pr(>|t|)    
(Intercept)                    -2.71604    0.10827 -25.085  < 2e-16 ***
factor(stage)2                  0.78141    0.14726   5.306 1.35e-07 ***
factor(stage)3                  0.80093    0.15250   5.252 1.80e-07 ***
factor(stage)4                  1.07293    0.17817   6.022 2.33e-09 ***
factor(histol)2                 1.45836    0.31780   4.589 4.96e-06 ***
factor(stage)2:factor(histol)2 -0.04743    0.43495  -0.109    0.913    
factor(stage)3:factor(histol)2  0.28064    0.41298   0.680    0.497    
factor(stage)4:factor(histol)2  0.90983    0.63774   1.427    0.154    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for quasibinomial family taken to be 1.000876)

Number of Fisher Scoring iterations: 4

> summary(svyglm(rel~factor(stage)*factor(histol),family=quasibinomial,design=gccs8))

Call:
svyglm(formula = rel ~ factor(stage) * factor(histol), design = gccs8, 
    family = quasibinomial)

Survey design:
calibrate(dccs2, phase = 2, formula = ~interaction(instit, stage, 
    rel))

Coefficients:
                               Estimate Std. Error t value Pr(>|t|)    
(Intercept)                    -2.71604    0.10878 -24.968  < 2e-16 ***
factor(stage)2                  0.78141    0.14729   5.305 1.35e-07 ***
factor(stage)3                  0.80093    0.15212   5.265 1.68e-07 ***
factor(stage)4                  1.07293    0.17905   5.993 2.77e-09 ***
factor(histol)2                 1.45836    0.31757   4.592 4.88e-06 ***
factor(stage)2:factor(histol)2 -0.04743    0.43432  -0.109    0.913    
factor(stage)3:factor(histol)2  0.28064    0.41231   0.681    0.496    
factor(stage)4:factor(histol)2  0.90983    0.63187   1.440    0.150    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for quasibinomial family taken to be 1.000876)

Number of Fisher Scoring iterations: 4

> 
> ## check subsets of calibrated designs.
> summary(svyglm(rel~factor(stage),
+                family=quasibinomial,design=subset(dccs8,histol==1)))

Call:
svyglm(formula = rel ~ factor(stage), design = subset(dccs8, 
    histol == 1), family = quasibinomial)

Survey design:
subset(dccs8, histol == 1)

Coefficients:
               Estimate Std. Error t value Pr(>|t|)    
(Intercept)     -2.7160     0.1083 -25.085  < 2e-16 ***
factor(stage)2   0.7814     0.1473   5.306 1.48e-07 ***
factor(stage)3   0.8009     0.1525   5.252 1.97e-07 ***
factor(stage)4   1.0729     0.1782   6.022 2.73e-09 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for quasibinomial family taken to be 1.001333)

Number of Fisher Scoring iterations: 4

Warning messages:
1: In `[.twophase2`(x, r, ) : 1 strata have only one PSU in this subset.
2: In summary.glm(g) :
  observations with zero weight not used for calculating dispersion
3: In summary.glm(glm.object) :
  observations with zero weight not used for calculating dispersion
4: In `[.twophase2`(design, nas == 0, ) :
  1 strata have only one PSU in this subset.
5: In `[.twophase2`(design, nas == 0, ) :
  1 strata have only one PSU in this subset.
> summary(svyglm(rel~factor(stage),
+                family=quasibinomial,design=subset(gccs8,histol==1)))

Call:
svyglm(formula = rel ~ factor(stage), design = subset(gccs8, 
    histol == 1), family = quasibinomial)

Survey design:
subset(gccs8, histol == 1)

Coefficients:
               Estimate Std. Error t value Pr(>|t|)    
(Intercept)     -2.7160     0.1082 -25.105  < 2e-16 ***
factor(stage)2   0.7814     0.1457   5.363 1.10e-07 ***
factor(stage)3   0.8009     0.1504   5.324 1.34e-07 ***
factor(stage)4   1.0729     0.1759   6.101 1.70e-09 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for quasibinomial family taken to be 1.001333)

Number of Fisher Scoring iterations: 4

Warning messages:
1: In summary.glm(g) :
  observations with zero weight not used for calculating dispersion
2: In summary.glm(glm.object) :
  observations with zero weight not used for calculating dispersion
> 
> 
> proc.time()
   user  system elapsed 
  0.840   0.057   0.896 
