TCC AMAN - apoio para cad Ederson

Referência: Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale,NJ: Lawrence Erlbaum.

book: Cohen, J. (1988)

library(pwr)
library(pwr2)

Usage pwr.chisq.test(w = NULL, N = NULL, df = NULL, sig.level = 0.05, power = NULL) Arguments

  w 
  Effect size
  N 
  Total number of observations
  df    
  degree of freedom (depends on the chosen test)
  sig.level 
  Significance level (Type I error probability)
  power 
  Power of test (1 minus Type II error probability)

see this chapter for details:

tamanho de amostra para o TCC

pwr.chisq.test(w=0.25,df=(2-1)*(2-1),sig.level=0.01, power=0.95)

     Chi squared power calculation 

              w = 0.25
              N = 285.0266
             df = 1
      sig.level = 0.01
          power = 0.95

NOTE: N is the number of observations

opcional

rr # alguns tamanhos de amostra pwr.chisq.test(w=0.3,df=(2-1)*(3-1),sig.level=0.05, power=0.90)


     Chi squared power calculation 

              w = 0.3
              N = 140.5993
             df = 2
      sig.level = 0.05
          power = 0.9

NOTE: N is the number of observations

rr pwr.chisq.test(w=0.3,df=(2-1)*(4-1),sig.level=0.05, power=0.90)


     Chi squared power calculation 

              w = 0.3
              N = 157.461
             df = 3
      sig.level = 0.05
          power = 0.9

NOTE: N is the number of observations

rr pwr.chisq.test(w=0.3,df=(2-1)*(5-1),sig.level=0.05, power=0.90)


     Chi squared power calculation 

              w = 0.3
              N = 171.1672
             df = 4
      sig.level = 0.05
          power = 0.9

NOTE: N is the number of observations

rr pwr.chisq.test(w=0.2,df=(2-1)*(3-1),sig.level=0.05, power=0.90)


     Chi squared power calculation 

              w = 0.2
              N = 316.3484
             df = 2
      sig.level = 0.05
          power = 0.9

NOTE: N is the number of observations

rr pwr.chisq.test(w=0.2,df=(2-1)*(4-1),sig.level=0.05, power=0.90)


     Chi squared power calculation 

              w = 0.2
              N = 354.2872
             df = 3
      sig.level = 0.05
          power = 0.9

NOTE: N is the number of observations

rr pwr.chisq.test(w=0.2,df=(2-1)*(5-1),sig.level=0.05, power=0.90)


     Chi squared power calculation 

              w = 0.2
              N = 385.1263
             df = 4
      sig.level = 0.05
          power = 0.9

NOTE: N is the number of observations

rr pwr.chisq.test(w=0.1,df=(2-1)*(3-1),sig.level=0.05, power=0.90)


     Chi squared power calculation 

              w = 0.1
              N = 1265.394
             df = 2
      sig.level = 0.05
          power = 0.9

NOTE: N is the number of observations

rr pwr.chisq.test(w=0.1,df=(2-1)*(4-1),sig.level=0.05, power=0.90)


     Chi squared power calculation 

              w = 0.1
              N = 1417.149
             df = 3
      sig.level = 0.05
          power = 0.9

NOTE: N is the number of observations

rr pwr.chisq.test(w=0.1,df=(2-1)*(5-1),sig.level=0.05, power=0.90)


     Chi squared power calculation 

              w = 0.1
              N = 1540.505
             df = 4
      sig.level = 0.05
          power = 0.9

NOTE: N is the number of observations
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