Running ‘testthat.R’ [72s/74s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(psycho)
  > 
  > test_check("psycho")
  ── 1. Error: If it works. (@test-analyze.glmerMod.R#9)  ────────────────────────
  'summary' is not an exported object from 'namespace:lmerTest'
  1: psycho::analyze(fit) at testthat/test-analyze.glmerMod.R:9
  2: analyze.glmerMod(fit)
  3: data.frame(lmerTest::summary(fit)$coefficients)
  4: lmerTest::summary
  5: getExportedValue(pkg, name)
  6: stop(gettextf("'%s' is not an exported object from 'namespace:%s'", name, getNamespaceName(ns)), 
         call. = FALSE, domain = NA)
  
  ── 2. Error: If it works. (@test-analyze.merMod.R#9)  ──────────────────────────
  object of type 'closure' is not subsettable
  1: psycho::analyze(x) at testthat/test-analyze.merMod.R:9
  2: analyze.merMod(x)
  3: analyze(fit)
  4: analyze.merMod(fit)
  5: lmerTest::lmer(formula, data)
  6: eval.parent(mc)
  7: eval(expr, p)
  8: eval(expr, p)
  9: lme4::lmer(formula = formula, data = data)
  10: eval(mc, parent.frame(1L))
  11: eval(mc, parent.frame(1L))
  12: lme4::lFormula(formula = formula, data = data, control = structure(list(optimizer = "bobyqa", 
         restart_edge = TRUE, boundary.tol = 1e-05, calc.derivs = TRUE, use.last.params = FALSE, 
         checkControl = list(check.nobs.vs.rankZ = "ignore", check.nobs.vs.nlev = "stop", 
             check.nlev.gtreq.5 = "ignore", check.nlev.gtr.1 = "stop", check.nobs.vs.nRE = "stop", 
             check.rankX = "message+drop.cols", check.scaleX = "warning", check.formula.LHS = "stop"), 
         checkConv = list(check.conv.grad = list(action = "warning", tol = 0.002, relTol = NULL), 
             check.conv.singular = list(action = "ignore", tol = 1e-04), check.conv.hess = list(
                 action = "warning", tol = 1e-06)), optCtrl = list()), class = c("lmerControl", 
     "merControl")))
  13: checkFormulaData(formula, data, checkLHS = control$check.formula.LHS == "stop")
  14: stopifnot(!checkLHS || length(as.formula(formula, env = denv)) == 3)
  15: withCallingHandlers(tryCatch(if (missE) ...elt(i) else eval(cl.i, envir = envir), 
         error = function(e) {
             e$call <- cl.i
             stop(e)
         }), warning = function(w) {
         w$call <- cl.i
         w
     })
  16: tryCatch(if (missE) ...elt(i) else eval(cl.i, envir = envir), error = function(e) {
         e$call <- cl.i
         stop(e)
     })
  17: tryCatchList(expr, classes, parentenv, handlers)
  18: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  19: value[[3L]](cond)
  
  ── 3. Error: If it works. (@test-analyze.merModLmerTest.R#9)  ──────────────────
  object of type 'closure' is not subsettable
  1: psycho::analyze(fit) at testthat/test-analyze.merModLmerTest.R:9
  2: analyze.merMod(fit)
  3: analyze(fit)
  4: analyze.merMod(fit)
  5: lmerTest::lmer(formula, data)
  6: eval.parent(mc)
  7: eval(expr, p)
  8: eval(expr, p)
  9: lme4::lmer(formula = formula, data = data)
  10: eval(mc, parent.frame(1L))
  11: eval(mc, parent.frame(1L))
  12: lme4::lFormula(formula = formula, data = data, control = structure(list(optimizer = "bobyqa", 
         restart_edge = TRUE, boundary.tol = 1e-05, calc.derivs = TRUE, use.last.params = FALSE, 
         checkControl = list(check.nobs.vs.rankZ = "ignore", check.nobs.vs.nlev = "stop", 
             check.nlev.gtreq.5 = "ignore", check.nlev.gtr.1 = "stop", check.nobs.vs.nRE = "stop", 
             check.rankX = "message+drop.cols", check.scaleX = "warning", check.formula.LHS = "stop"), 
         checkConv = list(check.conv.grad = list(action = "warning", tol = 0.002, relTol = NULL), 
             check.conv.singular = list(action = "ignore", tol = 1e-04), check.conv.hess = list(
                 action = "warning", tol = 1e-06)), optCtrl = list()), class = c("lmerControl", 
     "merControl")))
  13: checkFormulaData(formula, data, checkLHS = control$check.formula.LHS == "stop")
  14: stopifnot(!checkLHS || length(as.formula(formula, env = denv)) == 3)
  15: withCallingHandlers(tryCatch(if (missE) ...elt(i) else eval(cl.i, envir = envir), 
         error = function(e) {
             e$call <- cl.i
             stop(e)
         }), warning = function(w) {
         w$call <- cl.i
         w
     })
  16: tryCatch(if (missE) ...elt(i) else eval(cl.i, envir = envir), error = function(e) {
         e$call <- cl.i
         stop(e)
     })
  17: tryCatchList(expr, classes, parentenv, handlers)
  18: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  19: value[[3L]](cond)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 1).
  Rejecting initial value:
    Log probability evaluates to log(0), i.e. negative infinity.
    Stan can't start sampling from this initial value.
  Rejecting initial value:
    Log probability evaluates to log(0), i.e. negative infinity.
    Stan can't start sampling from this initial value.
  
  Gradient evaluation took 0.000115 seconds
  1000 transitions using 10 leapfrog steps per transition would take 1.15 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.947446 seconds (Warm-up)
                 0.838461 seconds (Sampling)
                 1.78591 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 2).
  Rejecting initial value:
    Log probability evaluates to log(0), i.e. negative infinity.
    Stan can't start sampling from this initial value.
  
  Gradient evaluation took 8.6e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.86 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.973983 seconds (Warm-up)
                 0.697993 seconds (Sampling)
                 1.67198 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 3).
  
  Gradient evaluation took 5.4e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.54 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.9633 seconds (Warm-up)
                 0.706389 seconds (Sampling)
                 1.66969 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 4).
  
  Gradient evaluation took 3.9e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.39 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 1.00511 seconds (Warm-up)
                 0.761756 seconds (Sampling)
                 1.76687 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 0.00013 seconds
  1000 transitions using 10 leapfrog steps per transition would take 1.3 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 5.03831 seconds (Warm-up)
                 5.34014 seconds (Sampling)
                 10.3784 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 7.7e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.77 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 5.21322 seconds (Warm-up)
                 4.74926 seconds (Sampling)
                 9.96248 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 0.000102 seconds
  1000 transitions using 10 leapfrog steps per transition would take 1.02 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 4.87673 seconds (Warm-up)
                 4.64952 seconds (Sampling)
                 9.52625 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 5.7e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.57 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 5.08224 seconds (Warm-up)
                 3.53713 seconds (Sampling)
                 8.61937 seconds (Total)
  
  The Crawford-Howell (1998) t-test suggests that the case partipant is significantly distinct from the control group (t(7) = 3.05, p < .05*).
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 1).
  
  Gradient evaluation took 8.3e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.83 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.169832 seconds (Warm-up)
                 0.195211 seconds (Sampling)
                 0.365043 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 2).
  
  Gradient evaluation took 7.5e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.75 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.158643 seconds (Warm-up)
                 0.183037 seconds (Sampling)
                 0.34168 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 3).
  
  Gradient evaluation took 6.7e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.67 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.168827 seconds (Warm-up)
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                 0.331496 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 4).
  
  Gradient evaluation took 5.1e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.51 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.166947 seconds (Warm-up)
                 0.159475 seconds (Sampling)
                 0.326422 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 5.8e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.58 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.114056 seconds (Warm-up)
                 0.10787 seconds (Sampling)
                 0.221926 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 2.9e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.29 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.115472 seconds (Warm-up)
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                 0.229214 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 3.5e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.35 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.135248 seconds (Warm-up)
                 0.121198 seconds (Sampling)
                 0.256446 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 2.3e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.23 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.125493 seconds (Warm-up)
                 0.107532 seconds (Sampling)
                 0.233025 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 9.2e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.92 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.384887 seconds (Warm-up)
                 0.376543 seconds (Sampling)
                 0.76143 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 5e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.5 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.372977 seconds (Warm-up)
                 0.39562 seconds (Sampling)
                 0.768597 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 5e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.5 seconds.
  Adjust your expectations accordingly!
  
  
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  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.369356 seconds (Warm-up)
                 0.360458 seconds (Sampling)
                 0.729814 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 4.7e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.47 seconds.
  Adjust your expectations accordingly!
  
  
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  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.314049 seconds (Warm-up)
                 0.375404 seconds (Sampling)
                 0.689453 seconds (Total)
  
  The Mellenbergh & van den Brink (1998) test suggests that the change is not significant (d = 8, 90% CI [1.06, 14.94], z = 1.90, p = 0.06<b0>).
  
  The Mellenbergh & van den Brink (1998) test suggests that the change is significant (d = 8, 90% CI [2.07, 13.93], z = 2.23, p < .05*).
  
  1
  ══ testthat results  ═══════════════════════════════════════════════════════════
  OK: 57 SKIPPED: 0 FAILED: 3
  1. Error: If it works. (@test-analyze.glmerMod.R#9) 
  2. Error: If it works. (@test-analyze.merMod.R#9) 
  3. Error: If it works. (@test-analyze.merModLmerTest.R#9) 
  
  Error: testthat unit tests failed
  Execution halted