Running ‘testthat.R’ [60s/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 0.000298 seconds
  1000 transitions using 10 leapfrog steps per transition would take 2.98 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.706516 seconds (Warm-up)
                 0.60288 seconds (Sampling)
                 1.3094 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 4.9e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.49 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.722079 seconds (Warm-up)
                 0.54587 seconds (Sampling)
                 1.26795 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 3).
  
  Gradient evaluation took 4.2e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.42 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.766527 seconds (Warm-up)
                 0.526654 seconds (Sampling)
                 1.29318 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' 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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   Elapsed Time: 0.726271 seconds (Warm-up)
                 0.553342 seconds (Sampling)
                 1.27961 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 0.000108 seconds
  1000 transitions using 10 leapfrog steps per transition would take 1.08 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 4.17784 seconds (Warm-up)
                 4.44729 seconds (Sampling)
                 8.62513 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  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: 4.61847 seconds (Warm-up)
                 4.14893 seconds (Sampling)
                 8.76741 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 6.5e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.65 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 4.2045 seconds (Warm-up)
                 4.00063 seconds (Sampling)
                 8.20513 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  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: 4.6166 seconds (Warm-up)
                 3.10051 seconds (Sampling)
                 7.71711 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 5.8e-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: 0.142782 seconds (Warm-up)
                 0.152233 seconds (Sampling)
                 0.295015 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 2).
  
  Gradient evaluation took 4.2e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.42 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.141481 seconds (Warm-up)
                 0.173982 seconds (Sampling)
                 0.315463 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 3).
  
  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: 0.135907 seconds (Warm-up)
                 0.146949 seconds (Sampling)
                 0.282856 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 4).
  
  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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   Elapsed Time: 0.140235 seconds (Warm-up)
                 0.145132 seconds (Sampling)
                 0.285367 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 4.9e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.49 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.118322 seconds (Warm-up)
                 0.114516 seconds (Sampling)
                 0.232838 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 3.1e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.31 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.127267 seconds (Warm-up)
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                 0.2433 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 2.7e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.27 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.129005 seconds (Warm-up)
                 0.114613 seconds (Sampling)
                 0.243618 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: 0.140426 seconds (Warm-up)
                 0.111154 seconds (Sampling)
                 0.25158 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 6.9e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.69 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.31798 seconds (Warm-up)
                 0.323953 seconds (Sampling)
                 0.641933 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: 0.318166 seconds (Warm-up)
                 0.308578 seconds (Sampling)
                 0.626744 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 4e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.4 seconds.
  Adjust your expectations accordingly!
  
  
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  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.314247 seconds (Warm-up)
                 0.289634 seconds (Sampling)
                 0.603881 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  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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  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.287358 seconds (Warm-up)
                 0.324443 seconds (Sampling)
                 0.611801 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