Running ‘testthat.R’ [61s/83s]
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 0.000217 seconds
  1000 transitions using 10 leapfrog steps per transition would take 2.17 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.686133 seconds (Warm-up)
                 0.648471 seconds (Sampling)
                 1.3346 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 3e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.3 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.771253 seconds (Warm-up)
                 0.557899 seconds (Sampling)
                 1.32915 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 3).
  
  Gradient evaluation took 4.4e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.44 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.782569 seconds (Warm-up)
                 0.529352 seconds (Sampling)
                 1.31192 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 4).
  
  Gradient evaluation took 3.3e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.33 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.751738 seconds (Warm-up)
                 0.550426 seconds (Sampling)
                 1.30216 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 0.000122 seconds
  1000 transitions using 10 leapfrog steps per transition would take 1.22 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 4.15759 seconds (Warm-up)
                 4.32303 seconds (Sampling)
                 8.48062 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 6.3e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.63 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 4.26405 seconds (Warm-up)
                 3.98007 seconds (Sampling)
                 8.24412 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 7e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.7 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 3.97955 seconds (Warm-up)
                 3.86506 seconds (Sampling)
                 7.84462 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 9.1e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.91 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 4.41897 seconds (Warm-up)
                 2.91686 seconds (Sampling)
                 7.33583 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 5.3e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.53 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.155783 seconds (Warm-up)
                 0.16691 seconds (Sampling)
                 0.322693 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 2).
  
  Gradient evaluation took 3.3e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.33 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.150925 seconds (Warm-up)
                 0.175808 seconds (Sampling)
                 0.326733 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 3).
  
  Gradient evaluation took 3e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.3 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.142691 seconds (Warm-up)
                 0.14762 seconds (Sampling)
                 0.290311 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 4).
  
  Gradient evaluation took 3.2e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.32 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.146169 seconds (Warm-up)
                 0.146111 seconds (Sampling)
                 0.29228 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 5.3e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.53 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.129843 seconds (Warm-up)
                 0.122941 seconds (Sampling)
                 0.252784 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 2.5e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.25 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.14184 seconds (Warm-up)
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                 0.271856 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 3.2e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.32 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.132318 seconds (Warm-up)
                 0.13081 seconds (Sampling)
                 0.263128 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  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: 0.152147 seconds (Warm-up)
                 0.130983 seconds (Sampling)
                 0.28313 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 7.3e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.73 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.320197 seconds (Warm-up)
                 0.318209 seconds (Sampling)
                 0.638406 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' 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: 0.335791 seconds (Warm-up)
                 0.329325 seconds (Sampling)
                 0.665116 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 4.5e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.45 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: 0.333814 seconds (Warm-up)
                 0.309435 seconds (Sampling)
                 0.643249 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 8.5e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.85 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
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  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.300963 seconds (Warm-up)
                 0.305694 seconds (Sampling)
                 0.606657 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