Running ‘testthat.R’ [73s/85s]
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 0.000285 seconds
  1000 transitions using 10 leapfrog steps per transition would take 2.85 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.876947 seconds (Warm-up)
                 0.802117 seconds (Sampling)
                 1.67906 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 4e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.4 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.924802 seconds (Warm-up)
                 0.680768 seconds (Sampling)
                 1.60557 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: 0.951925 seconds (Warm-up)
                 0.670303 seconds (Sampling)
                 1.62223 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 4).
  
  Gradient evaluation took 4.3e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.43 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.974115 seconds (Warm-up)
                 0.721872 seconds (Sampling)
                 1.69599 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 0.000172 seconds
  1000 transitions using 10 leapfrog steps per transition would take 1.72 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 5.23171 seconds (Warm-up)
                 5.60099 seconds (Sampling)
                 10.8327 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 0.000125 seconds
  1000 transitions using 10 leapfrog steps per transition would take 1.25 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 5.63815 seconds (Warm-up)
                 4.81202 seconds (Sampling)
                 10.4502 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 7.6e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.76 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 5.20246 seconds (Warm-up)
                 5.09156 seconds (Sampling)
                 10.294 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 9.3e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.93 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 5.92425 seconds (Warm-up)
                 3.99579 seconds (Sampling)
                 9.92005 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 8e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.8 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.199739 seconds (Warm-up)
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                 0.413268 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 2).
  
  Gradient evaluation took 4.8e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.48 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.189145 seconds (Warm-up)
                 0.214663 seconds (Sampling)
                 0.403808 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 3).
  
  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: 0.179524 seconds (Warm-up)
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                 0.342758 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: 0.177323 seconds (Warm-up)
                 0.172245 seconds (Sampling)
                 0.349568 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 6.6e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.66 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.137202 seconds (Warm-up)
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                 0.267637 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  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: 0.140909 seconds (Warm-up)
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                 0.264374 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 2.6e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.26 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.117741 seconds (Warm-up)
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                 0.243719 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 7.4e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.74 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.165594 seconds (Warm-up)
                 0.143793 seconds (Sampling)
                 0.309387 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 0.0001 seconds
  1000 transitions using 10 leapfrog steps per transition would take 1 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.395384 seconds (Warm-up)
                 0.399208 seconds (Sampling)
                 0.794592 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  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: 0.42646 seconds (Warm-up)
                 0.410978 seconds (Sampling)
                 0.837438 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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   Elapsed Time: 0.398542 seconds (Warm-up)
                 0.344937 seconds (Sampling)
                 0.743479 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' 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: 0.333663 seconds (Warm-up)
                 0.367199 seconds (Sampling)
                 0.700862 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