Running ‘testthat.R’ [58s/80s]
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 0.000202 seconds
  1000 transitions using 10 leapfrog steps per transition would take 2.02 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.67798 seconds (Warm-up)
                 0.614049 seconds (Sampling)
                 1.29203 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 5.2e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.52 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.747134 seconds (Warm-up)
                 0.554427 seconds (Sampling)
                 1.30156 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 3).
  
  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: 0.745152 seconds (Warm-up)
                 0.52595 seconds (Sampling)
                 1.2711 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: 0.775119 seconds (Warm-up)
                 0.547695 seconds (Sampling)
                 1.32281 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 0.000139 seconds
  1000 transitions using 10 leapfrog steps per transition would take 1.39 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 4.10452 seconds (Warm-up)
                 4.35883 seconds (Sampling)
                 8.46335 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: 4.29958 seconds (Warm-up)
                 3.96849 seconds (Sampling)
                 8.26807 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 0.000105 seconds
  1000 transitions using 10 leapfrog steps per transition would take 1.05 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 4.1303 seconds (Warm-up)
                 4.04128 seconds (Sampling)
                 8.17158 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: 4.20151 seconds (Warm-up)
                 2.9911 seconds (Sampling)
                 7.19261 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 5.5e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.55 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.152069 seconds (Warm-up)
                 0.157607 seconds (Sampling)
                 0.309676 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' 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: 0.148807 seconds (Warm-up)
                 0.176255 seconds (Sampling)
                 0.325062 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 3).
  
  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: 0.139845 seconds (Warm-up)
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                 0.283294 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: 0.137695 seconds (Warm-up)
                 0.139982 seconds (Sampling)
                 0.277677 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 4.6e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.46 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.111584 seconds (Warm-up)
                 0.115812 seconds (Sampling)
                 0.227396 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 3.6e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.36 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.109512 seconds (Warm-up)
                 0.110442 seconds (Sampling)
                 0.219954 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 3.6e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.36 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.106601 seconds (Warm-up)
                 0.113972 seconds (Sampling)
                 0.220573 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  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: 0.135592 seconds (Warm-up)
                 0.104626 seconds (Sampling)
                 0.240218 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  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: 0.338175 seconds (Warm-up)
                 0.320892 seconds (Sampling)
                 0.659067 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 3.8e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.38 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.32731 seconds (Warm-up)
                 0.321776 seconds (Sampling)
                 0.649086 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 4.1e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.41 seconds.
  Adjust your expectations accordingly!
  
  
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  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.31545 seconds (Warm-up)
                 0.298726 seconds (Sampling)
                 0.614176 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  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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  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.301712 seconds (Warm-up)
                 0.304268 seconds (Sampling)
                 0.60598 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: 56 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