Description Usage Arguments Details Value See Also Examples
Performs a power calculation for assessing a univariate dichotomous, trichotomous, or continuous intermediate biomarker response as a correlate of risk in the active treatment group in a clinical efficacy trial, accounting for the biomarker's measurement error and treatment efficacy. The statistical methods are described in [Gilbert, Janes, and Huang (2016). "Power/Sample Size Calculations for Assessing Correlates of Risk in Clinical Efficacy Trials."] Simulated data sets, extended to include placebo group and baseline immunogenicity predictor data, can be exported for harmonized assessment of biomarkerspecific treatment efficacy.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41  computePower(
nCasesTx,
nControlsTx,
nCasesTxWithS,
controlCaseRatio = NULL,
VEoverall,
risk0,
VElat0 = seq(0, VEoverall, len = 20),
VElat1 = rep(VEoverall, 20),
VElowest = NULL,
Plat0 = NULL,
Plat2 = NULL,
P0 = Plat0,
P2 = Plat2,
PlatVElowest = NULL,
sens = NULL,
spec = NULL,
FP0 = NULL,
FN2 = NULL,
M = 100,
alpha = 0.05,
sigma2obs = 1,
rho = 1,
biomType = c("continuous", "trichotomous", "dichotomous"),
cohort = FALSE,
p = NULL,
tpsMethod = c("PL", "ML", "WL"),
saveDir = NULL,
saveFile = "CoRpower.RData",
saveDataDir = NULL,
saveDataFile = "fullData.RData",
corr = NULL,
nCasesPla = NULL,
nControlsPla = NULL,
sensBIP = NULL,
specBIP = NULL,
FP0BIP = NULL,
FN2BIP = NULL,
P0BIP = P0,
P2BIP = P2
)

nCasesTx 
an integer vector specifying the observed (for a finished trial) or expected (for a trial in design stage) number of clinical endpoint cases between τ and τ_{max} in the active treatment group. Each value represents a distinct scenario for power assessment. 
nControlsTx 
an integer vector specifying the observed (for a finished trial) or expected (for a trial in design stage) number of controls with completed followup through τ_{max} and endpointfree at τ_{max} in the active treatment group. Each value represents a distinct scenario for power assessment. The ordering in 
nCasesTxWithS 
an integer vector specifying the observed (for a finished trial) or expected (for a trial in design stage) number of clinical endpoint cases between τ and τ_{max} in the active treatment group with an available biomarker response. Each value represents a distinct scenario for power assessment. The ordering must match 
controlCaseRatio 
an integer vector specifying the number of closeout controls sampled per case for biomarker measurement in the without replacement casecontrol sampling design (set to 
VEoverall 
a numeric value specifying the true overall treatment (vaccine) efficacy between τ and τ_{max} 
risk0 
a numeric value specifying the overall placebogroup endpoint risk between τ and τ_{max} 
VElat0 
a numeric vector specifying a grid of treatment (vaccine) efficacy levels in the latent lower protected subgroup for a dichotomous or trichotomous biomarker. Each value of 
VElat1 
a numeric vector specifying a grid of treatment (vaccine) efficacy levels in the latent medium protected subgroup for a trichotomous biomarker. Each value corresponds to one unique effect size (RR_t). The ordering must match 
VElowest 
a numeric vector specifying a grid of treatment (vaccine) efficacy levels in the latent lowestefficacy subgroup for a continuous biomarker. Default ranges from 
Plat0 
a numeric vector specifying the prevalence of the latent lower protected subgroup for a dichotomous or trichotomous biomarker (set to 
Plat2 
a numeric vector specifying the prevalence of the latent higher protected subgroup for a dichotomous or trichotomous biomarker (set to 
P0 
a numeric vector specifying the probability of low biomarker response for a dichotomous or trichotomous biomarker (set to 
P2 
a numeric vector specifying the probability of high biomarker response for a dichotomous or trichotomous biomarker (set to 
PlatVElowest 
a numeric vector specifying the prevalence of the latent lowestefficacy subgroup for a continuous biomarker (set to 
sens 
a numeric vector specifying the sensitivity, i.e., the probability of high biomarker response conditional on membership in the higher protected subgroup, for a dichotomous or trichotomous biomarker. Default is 
spec 
a numeric vector specifying the specificity, i.e., the probability of low biomarker response conditional on membership in the lower protected subgroup, of a dichotomous or trichotomous biomarker. Default is 
FP0 
a numeric vector specifying the false positive rate, i.e., the probability of high biomarker response conditional on membership in the lower protected subgroup, for a dichotomous or trichotomous biomarker. Default is 
FN2 
a numeric vector specifying the false negative rate, i.e., the probability of low biomarker response conditional on membership in the higher protected subgroup, for a dichotomous or trichotomous biomarker. Default is 
M 
an integer value specifying the number of simulated clinical trials. Default is 
alpha 
a numeric value specifying the twosided Wald test typeI error rate. Default is 
sigma2obs 
a numeric value specifying the variance of the observed continuous biomarker or of the dichotomous or trichotomous biomarker simulated using 'approach 2' (set to 
rho 
a numeric vector specifying distinct protectionrelevant fractions of 
biomType 
a character string specifying the biomarker type. Default is 
cohort 
a logical value for whether a casecohort Bernoulli sampling design is to be used. If 
p 
a numeric vector specifying the probability of sampling into the subcohort in the casecohort design ( 
tpsMethod 
a character string specifying the estimation method in the inverse probability weighted logistic regression model fit by the 
saveDir 
a character string specifying the path for a directory in which the output of the power calculation is to be saved. If 
saveFile 
a character vector specifying the name(s) of the 
saveDataDir 
a character string specifying the path for a directory in which the simulated data, including placebo group and baseline immunogenicity predictor (BIP) data, are to be saved. If 
saveDataFile 
a character vector specifying the name(s) of the 
corr 
a numeric vector in [1,1] specifying the correlation between a continuous baseline immunogenicity predictor (BIP) and the (underlying) continuous intermediate biomarker response ( 
nCasesPla 
an integer vector specifying the observed (for a finished trial) or expected (for a trial in design stage) number of clinical endpoint cases between τ and τ_{max} in the placebo group. Each value represents a distinct scenario matching 
nControlsPla 
an integer vector specifying the observed (for a finished trial) or expected (for a trial in design stage) number of controls with completed followup through τ_{max} and endpointfree at τ_{max} in the placebo group. Each value represents a distinct scenario matching 
sensBIP 
a numeric vector specifying "the sensitivity" of a dichotomous or trichotomous BIP, i.e., the probability of a high value of the BIP conditional on high biomarker response. Default is 
specBIP 
a numeric vector specifying "the specificity" of a dichotomous or trichotomous BIP, i.e., the probability of a low value of the BIP conditional on low biomarker response. Default is 
FP0BIP 
a numeric vector specifying "the false positive rate" of a dichotomous or trichotomous BIP, i.e., the probability of a high value of the BIP conditional on low biomarker response. Default is 
FN2BIP 
a numeric vector specifying "the false negative rate" of a dichotomous or trichotomous BIP, i.e., the probability of a low value of the BIP conditional on high biomarker response. Default is 
P0BIP 
a numeric vector specifying the probability of a low value of a dichotomous or trichotomous BIP. If unspecified, it is set to 
P2BIP 
a numeric vector specifying the probability of a high value of a dichotomous or trichotomous BIP. If unspecified, it is set to 
A number of calling arguments can be specified as vectors with each component specifying a distinct scenario for power assessment (saved in a separate .RData
file).
These are referred to as "varying arguments."
Some varying arguments occur in a group, where the length and order of all specified vectors in the group must match; others are the only varying argument in their group.
Only arguments belonging to a single group may be varied at a time; if two or more groups contain vector inputs, the function will treat such inputs as an error.
The following are the groups of varying arguments that can be vectorized:
nCasesTx
, nControlsTx
, and nCasesTxWithS
(together with nCasesPla
and nControlsPla
if simulated data sets are to be saved)
Plat0
, Plat2
, P0
, and P2
sens
, spec
, FP0
, and FN2
controlCaseRatio
rho
p
Arguments independent of biomarker type and sampling design: nCasesTx
, nControlsTx
, nCasesTxWithS
, VEoverall
, risk0
,
M
, alpha
, tpsMethod
, saveDir
, saveFile
.
Arguments specific to a trichotomous (or dichotomous) biomarker response: VElat0
, VElat1
, Plat0
, Plat2
, P0
,
P2
, biomType = "trichotomous"
(or "dichotomous"
)
Arguments for Approach 1: sens
, spec
, FP0
, FN2
Arguments for Approach 2: sigma2obs
, rho
Arguments specific to a continuous biomarker response: VElowest
, PlatVElowest
, sigma2obs
, rho
, biomType = "continuous"
Arguments for a casecontrol without replacement sampling design: controlCaseRatio
Arguments for a casecohort Bernoulli sampling design: cohort = TRUE
, p
To save output from the power calculations in an .RData
file, saveDir
must be specified. The default file name is CoRpower.RData
;
a different file name may be specified by saveFile
as a single character string, to which the value of the varying argument(s) will be appended for descriptive file naming purposes,
or, alternatively, a character vector may be specified with full file names (a single file will be produced for each value of the varying argument(s)).
To link power calculations for detecting a correlate of risk and a correlate of treatment efficacy, simulated data sets used in the power calculations
can be exported with placebogroup data, with a possible extension including BIP data, for harmonized use by methods assessing biomarkerspecific treatment efficacy.
The vignette "Algorithms for Simulating Placebo Group and Baseline Immunogenicity Predictor Data" provides more information on the algorithms and underlying assumptions for
simulating placebogroup and BIP data.
The exported data sets include treatment and placebo group data in the form of full rectangular data (i.e., disregarding biomarker subsampling), which enables the user to employ any preferred biomarker subsampling design.
To generate and export such data, saveDataDir
, nCasesPla
, and nControlsPla
must be specified. nCasesPla
and nControlsPla
must have
the same length and order of components as nCasesTx
, nControlsTx
, and nCasesTxWithS
.
If a BIP is to be included in the simulated data export, additional arguments are necessary.
If the biomarker is trichotomous and Approach 1 is used, sensBIP
, specBIP
, FP0BIP
, FN2BIP
, P0BIP
, and P2BIP
must be specified;
if the biomarker is trichotomous and Approach 2 is used, corr
, P0BIP
, and P2BIP
must be specified; if the biomarker is continuous, corr
must be specified.
Calling arguments pertaining to the simulation of the BIP in the exported data may also be specified as vectors, independently of the above varying arguments defining the power calculation scenarios for the active treatment group. Each component of these vectors results in the generation of a separate BIP variable, in the same order, in the output data. Some of these arguments occur in a group, where the length and order of all specified vectors in the group must match; others are the sole argument in their group. Only arguments belonging to a single group may be varied at a time; if two or more groups contain vector inputs, the function will treat such inputs as an error. The following are the groups of BIP arguments that can be vectorized:
sensBIP
, specBIP
, FP0BIP
, FN2BIP
P0BIP
, P2BIP
corr
The default file name for the outputted data sets is fullData.RData
. A different file name may be specified by saveDataFile
as a single character string, to which the value of the "varying argument" for the power calculations will be appended for descriptive file naming purposes,
or, alternatively, a character vector may be specified with full file names (a single file will be produced for each value of the varying argument(s)).
Note: if the "varying argument" is controlCaseRatio
or p
, only one file will be generated because these arguments do not affect
the simulation of the full data; therefore, saveDataFile
must be a character string in these cases.
If saveDir
is specified, an output list (named pwr
) for each power scenario is saved as an .RData
file. Otherwise, the function returns a list of lists,
where the outer list ranges over specified values of the varying argument(s) whose components denote distinct scenarios, and the inner list is the output list for each power scenario.
For a dichotomous or trichotomous biomarker, each output list has the following components:
power
: a numeric vector of fractions of simulated trials in which the null hypothesis H_0 is rejected. Each value of the vector corresponds to a value in the grid of treatment (vaccine) efficacies specified by VElat0
and VElat1
.
RRt
: a numeric vector of correlateofrisk relativerisk effect sizes. Each value of the vector corresponds to a value in the grid of treatment (vaccine) efficacies specified by VElat0
and VElat1
.
risk1_2
: a numeric vector of conditional endpoint risks given a high biomarker response in the active treatment group. Each value of the vector corresponds to a value in the grid of treatment (vaccine) efficacies specified by VElat0
and VElat1
.
risk1_0
: a numeric vector of conditional endpoint risks given a low biomarker response in the active treatment group. Each value of the vector corresponds to a value in the grid of treatment (vaccine) efficacies specified by VElat0
and VElat1
.
VElat2
: a numeric vector specifying a grid of treatment (vaccine) efficacy levels in the latent higher protected subgroup for a dichotomous or trichotomous biomarker
VElat0
: a numeric vector specifying a grid of treatment (vaccine) efficacy levels in the latent lower protected subgroup for a dichotomous or trichotomous biomarker
Plat2
: a numeric value specifying the prevalence of the latent higher protected subgroup for a dichotomous or trichotomous biomarker
Plat0
: a numeric value specifying the prevalence of the latent lower protected subgroup for a dichotomous or trichotomous biomarker
P2
: a numeric value specifying the probability of high biomarker response for a dichotomous or trichotomous biomarker
P0
: a numeric value specifying the probability of low biomarker response for a dichotomous or trichotomous biomarker
alphaLat
: a numeric vector of the log odds of the clinical endpoint in the subgroup of active treatment recipients with the latent x^{\ast}=0 (this coefficient estimate applies to a continuous biomarker)
betaLat
: a numeric vector of the log odds ratio of the clinical endpoint comparing two subgroups of active treatment recipients differing in the latent x^{\ast} by 1 (this coefficient estimate applies to a continuous biomarker)
sens
: a numeric vector of sensitivities (i.e., the probability of high biomarker response conditional on membership in the higher protected subgroup) of the observed dichotomous or trichotomous biomarker as a function of rho
spec
: a numeric vector of specificities (i.e., the probability of low biomarker response conditional on membership in the lower protected subgroup) of the observed dichotomous or trichotomous biomarker as a function of rho
FP0
: a numeric vector of false positive rates (i.e., the probability of high biomarker response conditional on membership in the lower protected subgroup) of the observed dichotomous or trichotomous biomarker as a function of rho
FN2
: a numeric vector of false negative rates (i.e., the probability of low biomarker response conditional on membership in the higher protected subgroup) of the observed dichotomous or trichotomous biomarker as a function of rho
NcompleteTx
: an integer value specifying nCasesTx
+ nControlsTx
, i.e., the number, observed or projected, of active treatment recipients at risk at τ with an observed endpoint or a completed followup through τ_{max}
nCasesTx
: an integer value specifying the number of clinical endpoint cases observed (or projected) between τ and τ_{max} in the active treatment group
nCasesTxWithS
: an integer value specifying the number of clinical endpoint cases observed (or projected) between τ and τ_{max} in the active treatment group with an available biomarker response
controlCaseRatio
: an integer specifying the number of controls sampled per case for
biomarker measurement in the without replacement casecontrol sampling design
VEoverall
: a numeric value specifying the overall treatment (vaccine) efficacy between τ and τ_{max}
risk0
: a numeric value specifying the overall placebogroup endpoint risk between τ and τ_{max}
alpha
: a numeric value specifying the twosided Wald test typeI error rate
rho
: a numeric vector specifying distinct protectionrelevant fractions of the variance of the observed biomarker
approach
: a number denoting whether Approach 1 or Approach 2 was used (1 if sens, spec, FP0, FN2 were specified in the input; 2 if rho and sigma2obs were specified in the input)
varyingArg
: a character string containing the name(s) and value(s) of the varying argument
For a continuous biomarker, each output list has the following components:
power
: a numeric vector of fractions of simulated trials in which the null hypothesis H_0 is rejected. Rows represent calculations for different values of rho
or nCasesTx
, depending on which is a vector. Columns represent calculations for the grid of treatment (vaccine) efficacy levels in the latent lowestefficacy subgroup, specified by VElowest
.
RRc
: a numeric vector of correlateofrisk relativerisk effect sizes as a function of the grid of treatment (vaccine) efficacy levels in the latent lowestefficacy subgroup, specified by VElowest
betaLat
: a numeric vector specifying the log odds ratio of the clinical endpoint comparing two subgroups of active treatment recipients differing in the latent x^{\ast} by 1 (this coefficient estimate applies to a continuous biomarker)
alphaLat
: a numeric vector specifying the the log odds of the clinical endpoint in the subgroup of active treatment recipients with the latent x^{\ast}=0 (this coefficient estimate applies to a continuous biomarker)
PlatVElowest
: a numeric value specifying the prevalence of the latent lowestefficacy subgroup for a continuous biomarker
VElowest
: a numeric vector specifying a grid of treatment (vaccine) efficacy levels in the latent lowestefficacy subgroup for a continuous biomarker
sigma2obs
: a numeric value specifying the variance of the observed continuous biomarker or of the dichotomous or trichotomous biomarker simulated using 'approach 2'
NcompleteTx
: an integer value specifying nCasesTx
+ nControlsTx
, i.e., the number, observed or projected, of active treatment recipients at risk at τ with an observed endpoint or a completed followup through τ_{max}
nCasesTx
: an integer value specifying the number of clinical endpoint cases observed (or projected) between τ and τ_{max} in the active treatment group
nCasesTxWithS
: an integer value specifying the number of clinical endpoint cases observed (or projected) between τ and τ_{max} in the active treatment group with an available biomarker response
controlCaseRatio
: an integer value specifying the number of controls sampled per case for biomarker measurement in the without replacement casecontrol sampling design
VEoverall
: a numeric value specifying the overall treatment (vaccine) efficacy between τ and τ_{max}
risk0
: a numeric value specifying the overall placebogroup endpoint risk between τ and τ_{max}
alpha
: a numeric value specifying the twosided Wald test typeI error rate
rho
: a numeric vector specifying distinct protectionrelevant fractions of the variance of the observed biomarker
varyingArg
: a character string containing the name(s) and value(s) of the varying argument
If saveDataDir
is specified, the simulated data, including placebo group and BIP data, are saved in one or more .RData
file(s)
containing a list of lists of data frames.
The components of the outer list consist each of one MonteCarlo iteration of simulated data for all values of VElat0
or VElat1
if
the biomarker is trichotomous, or of VElowest
if the biomarker is continuous. Each data frame corresponds to one simulated trial.
computeN
, plotPowerTri
, plotPowerCont
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148  ## Trichotomous biomarker, Approach 1, varying sens and spec ##
## Specify sens, spec, FP0, FN2
nCasesTx < 32
nControlsTx < 1000
nCasesTxWithS < 32
controlCaseRatio < 5
VEoverall < 0.75
risk0 < 0.034
VElat0 < seq(0, VEoverall, len=20) # 20 data points for the power curve
VElat1 < rep(VEoverall, 20)
Plat0 < 0.2
Plat2 < 0.6
P0 < Plat0 # different values of P0 can be set
P2 < Plat2 # different values of P2 can be set
sens < spec < c(1, 0.9, 0.8, 0.7)
FP0 < FN2 < rep(0, 4)
M < 5
alpha < 0.05
biomType < "trichotomous"
computePower(nCasesTx=nCasesTx, nControlsTx=nControlsTx, nCasesTxWithS=nCasesTxWithS,
controlCaseRatio=controlCaseRatio, VEoverall=VEoverall,
risk0=risk0, VElat0=VElat0, VElat1=VElat1, Plat0=Plat0,
Plat2=Plat2, P0=P0, P2=P2, M=M, alpha=alpha, spec=spec,
FP0=FP0, sens=sens, FN2=FN2, biomType=biomType)
## Not run:
## Trichotomous biomarker, Approach 2, varying rho ##
## Saving simulated data (including placebo and BIP data)
## Specify rho, sigma2obs, saveDataDir, saveDataFile, corr
nCasesTx < 32
nControlsTx < 1000
nCasesTxWithS < 32
controlCaseRatio < 5
VEoverall < 0.75
risk0 < 0.034
VElat0 < seq(0, VEoverall, len=20)
VElat1 < rep(VEoverall, 20)
Plat0 < 0.2
Plat2 < 0.6
P0 < Plat0
P2 < Plat2
M < 5
alpha < 0.05
sigma2obs < 1
rho < c(1, 0.9, 0.7, 0.5)
biomType < "trichotomous"
saveDataDir < "~/myDir"
saveDataFile < "myDataFile.RData"
corr < 0.7
computePower(nCasesTx=nCasesTx, nControlsTx=nControlsTx, nCasesTxWithS=nCasesTxWithS,
controlCaseRatio=controlCaseRatio, VEoverall=VEoverall, risk0=risk0,
VElat0=VElat0, VElat1=VElat1, Plat0=Plat0, Plat2=Plat2, P0=P0, P2=P2,
M=M, alpha=alpha, sigma2obs=sigma2obs, rho=rho, biomType=biomType,
saveDataDir=saveDataDir, saveDataFile=saveDataFile, corr=corr)
## dichotomous biomarker, Approach 2, varying rho ##
## Plat0 + Plat2 = 1
nCasesTx < 32
nControlsTx < 1000
nCasesTxWithS < 32
controlCaseRatio < 5
VEoverall < 0.75
risk0 < 0.034
VElat0 < seq(0, VEoverall, len=20) # 20 data points for the power curve
VElat1 < rep(0, 20) # will not be used by function
Plat0 < 0.25
Plat2 < 1  Plat0
P0 < Plat0
P2 < Plat2
M < 5
alpha < 0.05
sigma2obs < 1
rho < c(1, 0.9, 0.7, 0.5)
biomType < "dichotomous"
computePower(nCasesTx=nCasesTx, nControlsTx=nControlsTx, nCasesTxWithS=nCasesTxWithS,
controlCaseRatio=controlCaseRatio, VEoverall=VEoverall, risk0=risk0,
VElat0=VElat0, VElat1=VElat1, Plat0=Plat0, Plat2=Plat2, P0=P0, P2=P2,
M=M, alpha=alpha, sigma2obs=sigma2obs, rho=rho, biomType=biomType)
## Continuous biomarker, varying rho ##
nCasesTx < 32
nControlsTx < 1000
nCasesTxWithS < 32
controlCaseRatio < 5
VEoverall < 0.75
risk0 < 0.034
PlatVElowest < 0.2
VElowest < seq(0, VEoverall, len=20)
M < 5
alpha < 0.05
sigma2obs < 1
rho < c(1, 0.9, 0.7, 0.5)
biomType < "continuous"
computePower(nCasesTx=nCasesTx, nControlsTx=nControlsTx, nCasesTxWithS=nCasesTxWithS,
controlCaseRatio=controlCaseRatio, VEoverall=VEoverall, risk0=risk0,
PlatVElowest=PlatVElowest, VElowest=VElowest, M=M, alpha=alpha,
sigma2obs=sigma2obs, rho=rho, biomType=biomType)
## Continuous biomarker, casecohort sampling design, varying p ##
nCasesTx < 32
nControlsTx < 1000
nCasesTxWithS < 32
VEoverall < 0.75
risk0 < 0.034
PlatVElowest < 0.2
VElowest < seq(0, VEoverall, len=20)
M < 5
alpha < 0.05
sigma2obs < 1
rho < 0.9
biomType < "continuous"
cohort < TRUE
p < c(0.01, 0.02, 0.03)
computePower(nCasesTx=nCasesTx, nControlsTx=nControlsTx, nCasesTxWithS=nCasesTxWithS,
VEoverall=VEoverall, risk0=risk0, PlatVElowest=PlatVElowest,
VElowest=VElowest, M=M, alpha=alpha, sigma2obs=sigma2obs,
rho=rho, biomType=biomType, cohort=cohort, p=p)
## Continuous biomarker, saving output, varying sample sizes ##
nCasesTx < 32
nControlsTx < 1000
nCasesTxWithS < 32
controlCaseRatio < 5
VEoverall < 0.75
risk0 < 0.034
PlatVElowest < 0.2
VElowest < seq(0, VEoverall, len=20)
M < 5
alpha < 0.05
sigma2obs < 1
rho < c(1, 0.9, 0.7, 0.5)
biomType < "continuous"
saveDir < "~/myDir"
saveFile < "MyFile.RData"
computePower(nCasesTx=nCasesTx, nCasesTxWithS=nCasesTxWithS, nControlsTx=nControlsTx,
controlCaseRatio=controlCaseRatio, VEoverall=VEoverall,
risk0=risk0, PlatVElowest=PlatVElowest, VElowest=VElowest,
M=M, alpha=alpha, sigma2obs=sigma2obs, rho=rho,
biomType=biomType, saveDir=saveDir, saveFile=saveFile)
## End(Not run)

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