Acute and Residual Effects of Caffeinated Beer: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Acute and Residual Effects of Caffeinated Beer (NCT00515294), a randomized phase 1, phase 2 study. The primary outcome is Lane Position Deviation.

2. Clinical Question

3. Trial Design

The registry describes a randomized, triple-masked study with a factorial model and lists phase 1 and phase 2. Its summary characterizes the design as a double placebo-controlled 2 X 2 factorial study. The four conditions combine the presence or absence of alcohol with the presence or absence of caffeine: caffeinated alcoholic beer, non-caffeinated alcoholic beer, caffeinated non-alcoholic beer, and non-caffeinated non-alcoholic beer. The record does not explain the difference between its triple-masking label and the double placebo-controlled wording in the summary.

The study was designed to examine acute and residual effects on simulated driving. The recorded primary outcome is lane position deviation at 30 minutes post dosing. The posted secondary outcome is the Psycho-motor Vigilance Test (PVT), also at 30 minutes post dosing. The study summary says that, under the alcohol conditions, participants would receive enough alcoholic beverage to attain a blood alcohol concentration of .12 g%. The registry does not post participant-level achieved concentrations or a separate analysis of residual effects.

Recorded enrollment is 154. The study summary describes 144 intended participants, including undergraduate and graduate students and recent college graduates. The arm counts differ by outcome: the primary outcome groups have 28, 35, 26, and 32 participants, while the secondary outcome groups have 29, 36, 27, and 35. The primary outcome description notes that six participants’ simulator data were excluded because the simulator did not work properly. Reasons for other differences in outcome-specific counts are not reported in the registry record.

The primary comparisons use the caffeinated alcoholic beer group as the reference and compare each other group with it. Although the four conditions are factorial in structure, the registry does not report a factorial-effect analysis, an interaction analysis, or adjusted models. The original sample-size justification, allocation procedures in detail, and statistical analysis plan are not reported in the registry record.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Driver simulator did not work properly for 6 participants. Their data are not included.

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

Population: We compared participants across groups by age and sex.

6. Primary Endpoint

The registry lists the primary outcome as Lane Position Deviation, measured over 30 minutes post dosing.

Lane position deviation records the car’s position relative to the center line in the driver simulator, in feet. A value of 0 indicates no deviation from the center line. Negative values indicate deviation to the right, with the car closer to the road edge while remaining within the lane. Positive values indicate deviation to the left, toward the oncoming-traffic side and closer to the road edge. This signed scale matters: the direction of a value indicates which side of the center line the car was on, rather than simply representing a measure of distance without direction.

The endpoint is a continuous measure, and the registry reports a mean and standard deviation for each group at 30 minutes post dosing. A simulator-based measure gives researchers a way to describe lane position under a controlled study task. It is not itself a direct report of real-world driving, and a group mean does not describe every participant’s performance. The record does not report a clinically meaningful threshold for the measure or explain how a particular difference in feet should be interpreted in practical terms.

The primary comparison asks how each non-reference group’s mean differs from the caffeinated alcoholic beer group. Because the outcome is signed, interpretation should consider both the direction of the difference and the fact that all four posted group means are negative. The mean and standard deviation summarize the observed data, while the confidence intervals around comparisons show uncertainty in the estimated mean differences. Neither summary alone describes the full distribution of individual driving-simulator measurements.

7. Results Posted in the Registry

• 2Non-Caffeinated Alcoholic Beer: mean -1.36 versus -1.25 on control; difference -0.11 (95% CI -0.47 to 0.25), standardized effect d = -0.15; z-test p = 0.550.
• 3Caffeinated Non-Alcoholic Beer: mean -1.22 versus -1.25 on control; difference 0.03 (95% CI -0.27 to 0.33), standardized effect d = 0.05; z-test p = 0.847.
• 4Non-Alcoholic, Non-Caffeinated Beer: mean -1.21 versus -1.25 on control; difference 0.04 (95% CI -0.31 to 0.39), standardized effect d = 0.06; z-test p = 0.823.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Psycho-motor Vigilance Test (PVT)

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • 2Non-Caffeinated Alcoholic Beer: mean 293.30 versus 278.70 on control; difference 14.60 (95% CI -8.28 to 37.48), standardized effect d = 0.31; z-test p = 0.211.
  • 3Caffeinated Non-Alcoholic Beer: mean 233.10 versus 278.70 on control; difference -45.60 (95% CI -64.53 to -26.67), standardized effect d = -1.23; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between 2Non-Caffeinated Alcoholic Beer and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for 3Caffeinated Non-Alcoholic Beer than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The posted secondary outcome is the Psycho-motor Vigilance Test at 30 minutes post dosing. Across its displayed group summaries, the two alcohol groups have higher mean reaction-time values than the two non-alcoholic groups, while the two caffeinated and non-caffeinated comparisons within those broad pairs show a different pattern. The registry results do not report a complete factorial analysis that would separate alcohol, caffeine, and any interaction, so this overall pattern is descriptive rather than a formal estimate of each factor’s contribution.

The secondary endpoint adds a different view of performance from lane position deviation. The primary result concerns the car’s position relative to the center line in a driving simulator; the secondary result is a continuous vigilance measure in milliseconds. A pattern in one outcome need not match a pattern in the other, because the outcomes measure different aspects of performance. The secondary findings therefore do not negate or confirm the primary comparisons. They provide context about another recorded measure at the same post-dosing time point.

The registry displays unadjusted comparisons for the secondary outcome, and the record lists no reported secondary analyses. In general, testing multiple outcomes and contrasts increases the chance that some results will look unusual by chance. Without a reported multiplicity plan, these secondary results should carry less weight than a prespecified primary analysis would, particularly if the comparisons were selected after examining the data. The registry does not report whether the outcome hierarchy or analyses were prespecified, so that possibility cannot be resolved from this record.

As with the primary outcome, group summaries do not show individual variation, and differences in outcome-specific participant counts mean that not every displayed summary is based on the same number of participants. Reasons for these differences are not reported. The secondary results can be used to describe the posted data, but they should not be treated as independent confirmation of a causal explanation or as evidence that one component of the factorial design accounts for the pattern.

Secondary outcomes registered for this trial, for reference (only those above were recalculated):

• Psycho-motor Vigilance Test (PVT)

9. Statistical Interpretation

10. Statistical Methods Explained

The posted outcome is continuous, so the registry reports a group mean and standard deviation. The comparison results give a mean difference for each non-reference group against the caffeinated alcoholic beer group, together with a confidence interval and an unadjusted p-value. These summaries answer related but different questions: the mean difference gives the estimated direction and size of the contrast on the feet scale, the confidence interval conveys uncertainty around that estimate, and the p-value describes how incompatible the data are with a zero difference under the comparison’s statistical assumptions.

What does a mean difference represent?

In general, a difference between two group means is calculated by subtracting one group mean from the other, with the sign determined by the comparison order. Here the posted comparisons identify the caffeinated alcoholic beer group as the reference and show the difference for each other group. A negative estimate means the other group’s mean is lower on the signed lane-position scale; a positive estimate means it is higher. Because the scale distinguishes left from right, that direction should not automatically be translated into better or worse driving. The outcome description gives the physical direction of the deviation, but the registry does not supply a threshold for judging its practical importance.

The standard deviation describes spread among observations within a group. It is not the same as the standard error of a mean or the confidence interval for a difference. In general, a standard deviation concerns variation between individual observations, whereas the standard error concerns uncertainty in an estimated mean. The posted arm summaries report standard deviations; the comparisons use group sample sizes and pooled variability in the displayed calculation. The registry does not report an adjusted regression model for these primary comparisons.

What do the confidence intervals add?

In general, a confidence interval gives a range of estimates compatible with the observed data under a specified statistical procedure. It should not be read as a range containing a fixed proportion of individual participants’ measurements. For these results, each interval is for a mean difference, not for the distribution of lane positions. An interval that spans zero indicates that the data do not rule out a zero mean difference at the corresponding conventional two-sided level; it does not prove that there is no effect or that the groups are equivalent.

Confidence intervals also help assess precision. A narrow interval indicates more precision than a wide interval on the same scale, although precision alone does not establish practical importance. The primary intervals span values on both sides of zero. The record does not specify a threshold separating small from important lane-position differences, so the practical meaning of the interval endpoints cannot be determined from the registry result alone.

How should the p-values be read?

In general, a p-value is calculated under a null hypothesis and statistical model. It describes how unusual results at least as incompatible with that null would be if the null and model assumptions held. It is not the probability that the null hypothesis is true, nor is it a direct measure of the size or importance of a difference. The primary p-values are explicitly unadjusted. The registry does not report whether these comparisons were prespecified or how any multiple-comparison issue was handled.

The posted p-values are consistent with the confidence intervals in the sense that the primary intervals include zero and the p-values are not small. That correspondence does not replace attention to the estimates and intervals. In general, a result can be imprecise even when its point estimate is close to zero, and absence of a small p-value is not affirmative evidence of no meaningful difference.

What does the factorial structure imply?

In general, a 2 X 2 factorial design combines two factors, each with two levels. Here the conditions correspond to alcohol present or absent and caffeine present or absent. Such a design can potentially examine the separate contribution of each factor and whether their effects depend on one another. That requires an analysis that uses the factorial structure and specifies how the factors and any interaction are modeled. The registry displays comparisons of each non-reference arm with the caffeinated alcoholic beer arm, but does not report those separate factorial estimates or an interaction test. The posted pairwise contrasts should therefore not be described as a complete factorial analysis.

The record labels the trial randomized and triple-masked, and the summary describes it as double placebo-controlled. Randomization and masking are design features intended to reduce particular kinds of bias, but the registry does not report details of the procedures or whether masking was assessed. The record also does not report the allocation ratio or an analysis plan. These omissions limit what can be said about how the planned analysis was specified and carried out.

Why can over-dispersion matter?

In general, over-dispersion refers to observed variability greater than a statistical model expects. It can make uncertainty estimates too small if a model fails to account for extra variability, particularly in outcome settings where variance is constrained by a specific distribution. The primary endpoint is a continuous measure, and the posted summaries include standard deviations; the registry does not report an over-dispersion assessment or a model for it. This general concept should not be mistaken for a finding that over-dispersion occurred in this study.

The registry reports no statistical analysis details that would allow a reader to independently assess every modeling choice. The numerical comparison summaries are therefore best read as the posted results, with the displayed unadjusted estimates and intervals, rather than as a full account of an analysis plan. The study’s own sample-size justification, missing-data approach, and any interim analyses are not reported in the registry record.

11. Confidence Intervals and Precision

The primary comparisons have confidence intervals that extend both below and above zero. For non-caffeinated alcoholic beer versus caffeinated alcoholic beer, the mean difference is -0.11 feet, and the interval runs from -0.471 to 0.251. For caffeinated non-alcoholic beer versus the reference, the difference is 0.03 feet, with an interval from -0.274 to 0.334. For non-alcoholic, non-caffeinated beer versus the reference, the difference is 0.04 feet, with an interval from -0.310 to 0.390.

In general, an interval’s width describes precision on the outcome scale: a wider interval permits a broader range of plausible mean differences. Here each interval includes zero, and each also allows differences in either direction. This means the results do not pin down a single precise value for any of the three contrasts. The point estimates are close to zero, but the intervals should be considered alongside them rather than treating the point estimates as definitive.

The intervals are for differences in group means, not for individual participants’ lane positions. They do not imply that most participants had values within the interval, nor do they show the range of individual driving behavior. The group standard deviations describe a different feature of the data: observed spread within each arm. No clinically or operationally meaningful threshold is reported, so the registry does not establish whether particular values within these intervals would be important in practice.

The posted confidence intervals also do not account for every possible source of uncertainty. The registry does not report adjustment for multiple comparisons, a factorial model, or sensitivity analyses for missing simulator data. The six simulator records excluded because the device did not work properly may affect interpretation, but the record does not give information that would quantify such an effect. The intervals should therefore be read as precision summaries for the posted comparisons, not as a complete account of uncertainty about all possible study questions.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The sample-size section is a planning illustration based on the observed effect, not the trial’s original design justification. For these continuous outcomes, the figures are participants per arm, not total event counts. The planning assumptions listed are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set to the stated fraction of the observed effect. The original trial’s own sample-size assumptions are not reported in the registry record.

The 80% power column gives the illustrated number of participants per arm for a design with an 80% chance of detecting the specified effect under the planning assumptions, if that effect and those assumptions hold. The 90% power column gives the corresponding illustration for 90% power. These are prospective planning quantities, not a measure of how much power the completed trial had. This is not observed power.

Each row scales the effect used for the illustration: the observed effect, 75% of that effect, or 50% of that effect. A smaller effect is harder to distinguish from random variation, so it requires more participants under the same assumptions. The rows should be interpreted as alternative planning scenarios rather than claims that any particular effect is clinically important or will occur in a future study.

The numbers in the table are calculated from the posted summary statistics and apply to a two-arm comparison at a time. They do not represent the sample size required for a full factorial analysis, multiple comparisons, or the original trial’s complete design. The registry does not report the sample-size calculation used when the study was planned. A plotted curve, if shown alongside the table, visualizes the same planning relationship and should be read with the same assumptions and limitations.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -0.110; pooled standard deviation σ = 0.753.
2. n = 2 × (1.96 + 0.842)² × 0.753² / -0.110² = 736.1, rounded up to 737 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
delta <- -0.11                      # observed difference in means
sigma <- 0.753262847904227                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(515294)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 737 (80% power), 986 (90% power)
 75% of observed effect: n per arm = 1,309 (80% power), 1,752 (90% power)
 50% of observed effect: n per arm = 2,945 (80% power), 3,942 (90% power)
power.t.test: 737.1 
Simulated power at n = 737 per arm: 0.799 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Multiplicity, Missing Data and Analysis Populations

The posted results include a primary endpoint with three comparisons against one reference group and a secondary endpoint with displayed comparisons. Each comparison is reported without adjustment. The registry record does not state whether a multiplicity procedure was planned, whether a particular comparison was designated as the principal contrast, or how the results should be interpreted across the set of outcomes. Without that information, the unadjusted p-values should be treated as results for individual contrasts, not as controlling the chance of a false positive across the whole set of tests.

The study is described as factorial, but the registry does not report a model estimating the main effects of alcohol and caffeine or their interaction. The displayed comparisons answer narrower questions: each non-reference group is contrasted with caffeinated alcoholic beer. A reader should not infer that the displayed pairwise results exhaust the scientific questions that a factorial design might address.

The primary outcome description states that six participants’ simulator data were not included because the driver simulator did not work properly. The record does not report whether these exclusions were balanced across groups, whether any other primary measurements were missing, or whether imputation or sensitivity analyses were used. It also does not provide a detailed analysis-population definition. The differing participant counts for the primary and secondary outcome summaries are visible in the posted results, but reasons beyond the stated simulator problem are not reported in the registry record.

The record does not report an interim-analysis plan, stopping rules, or details about how missing data were handled. It also does not report a detailed statistical analysis plan or whether the comparisons were specified before the results were examined. These are reporting gaps, not evidence that a particular procedure was or was not used. They limit assessment of the planned analysis, the handling of multiple comparisons, and the potential effect of incomplete outcome data.

15. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 5% reporting threshold.

The adverse-event summary lists four groups and reports zero serious adverse events, zero other adverse events, and zero deaths in each group. The numbers at risk are listed separately by group: 29 for caffeinated alcohol, 36 for non-caffeinated alcohol, 27 for caffeinated non-alcoholic beer, and 35 for non-alcoholic, non-caffeinated beer. These are the registry’s recorded safety figures; they are not a comparison adjusted for differences in group size or duration of observation.

In general, zero recorded events in a group means that no events of that category were reported for the listed group in this record. It does not prove that the true risk is zero or that no unrecorded events occurred. The registry does not provide event definitions, observation duration for safety reporting, details of collection, or a fuller narrative of non-serious events. The record lists no serious adverse-event terms. Safety interpretation should remain limited to these reported counts and the information accompanying them.

16. What the Result Does, and Does Not, Mean

The posted primary data show mean lane-position deviations in four randomized groups and unadjusted comparisons of three groups against caffeinated alcoholic beer. Each primary comparison’s confidence interval includes zero. These results do not provide a precise estimate that excludes no mean difference for any of those contrasts. They also do not establish that the groups are equivalent: the registry does not report an equivalence margin, and a non-significant comparison is not the same as evidence of equivalence.

The outcome is a simulator measure at a single stated time point, 30 minutes post dosing. Its signed scale distinguishes deviation to the right from deviation to the left, and the record describes both directions in relation to the lane and road edge. The posted group means are summaries, not descriptions of every participant. They do not show individual driving behavior, real-world driving outcomes, or the persistence of any difference beyond the reported time point.

The study summary describes a target blood alcohol concentration of .12 g% under alcohol conditions, but the registry does not report achieved concentrations. The posted comparisons also do not include a factorial analysis estimating separate alcohol and caffeine effects or their interaction. Accordingly, the results cannot be used from this record alone to attribute a pattern to one component of the study conditions.

The PVT is a separate secondary measure, and its overall pattern does not answer the same question as lane position deviation. It can inform a descriptive account of another recorded outcome, but unadjusted secondary comparisons carry less weight when the multiplicity plan and prespecified outcome hierarchy are not reported. The registry’s safety figures list no reported serious or other adverse events and no deaths; those counts do not establish the absence of risk.

In general, these data describe a specific randomized simulator study and its posted outcomes. They do not support medical or driving advice, a conclusion about real-world safety, or a claim about all people or all caffeinated alcoholic products. The registry record does not report the information needed to make those broader interpretations.

17. Why This Trial Matters Statistically

This trial is statistically interesting because its four conditions form a 2 X 2 factorial structure: alcohol and caffeine are each present or absent. That structure can be useful for examining the individual factors and whether their effects depend on one another. Yet the registry’s posted primary comparisons use one arm as the reference and compare each other arm with it. Those contrasts do not, by themselves, provide the full factorial decomposition. The distinction between a design structure and the analysis actually reported is important when reading clinical trial results.

The primary endpoint also illustrates why outcome definitions matter. Lane-position deviation is signed: negative and positive values refer to opposite sides of the center line. A mean difference near zero can be interpreted only in relation to that scale and the group variability. It should not automatically be translated into a simple judgment about driving quality. Clear definitions help readers avoid treating directional data as a generic measure of distance.

Uncertainty is central to this record. The primary confidence intervals include zero and allow differences in both directions. The estimates alone are not enough to establish equivalence, and the registry does not provide a threshold for practical importance. The posted results show how a point estimate, uncertainty interval, and unadjusted p-value contribute different pieces of information.

Finally, outcome-specific participant counts and the stated simulator failure show why analysis populations and missing-data reporting matter. The registry gives a reason for six primary simulator records being excluded, but does not report the broader missing-data approach or sensitivity analyses. These details affect how fully readers can assess the reported comparisons. The planning illustrations also make a useful distinction between future design calculations and the study’s original design assumptions, which are not reported.

18. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

The registry record leaves several trial-specific questions unresolved. It describes both a triple-masked study and a double placebo-controlled design, but does not explain the masking procedures or reconcile those descriptions. It does not report the original sample-size justification, the statistical analysis plan, interim analyses, or stopping rules. The planned target in the study summary and the recorded enrollment are both stated, but the record does not explain the difference between them.

For the primary endpoint, the record says that six participants’ simulator data were not included because the device did not work properly. It does not report which groups were affected, how missing data were otherwise handled, or whether sensitivity analyses were performed. Primary outcome counts differ across arms, and the secondary outcome counts differ from the primary counts. Explanations for those other outcome-specific differences are not reported in the registry record.

The posted primary comparisons are unadjusted pairwise comparisons against one reference group. There is no reported factorial analysis, interaction estimate, multiplicity adjustment, or prespecified hierarchy of outcomes. The PVT is the only secondary outcome listed, and its reported comparisons are also unadjusted. The registry record does not report a threshold for meaningful differences in either endpoint or detailed information about the distribution of measurements.

The simulator outcome was assessed at 30 minutes post dosing. Although the study summary describes acute and residual effects as its aim, the registry does not post separate residual-effect results in the information. It also does not report achieved blood alcohol concentrations. These limits mean the posted summaries should be read as results for the listed outcomes and time point, rather than as a complete account of every intended study question.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Acute and Residual Effects of Caffeinated Beer — NCT00515294.
• Registry record last updated 2017-06-28; status last verified 2017-05.
• Results first posted 2017-06-28.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

22. Record Summary

This completed randomized study is listed as phase 1 and phase 2, with a factorial model and triple masking. Its summary describes a double placebo-controlled 2 X 2 design comparing caffeinated alcoholic beer, non-caffeinated alcoholic beer, caffeinated non-alcoholic beer, and non-caffeinated non-alcoholic beer. Recorded enrollment is 154.

The primary outcome is lane position deviation in a driver simulator at 30 minutes post dosing. The registry posts group means, standard deviations, and unadjusted comparisons against the caffeinated alcoholic beer group. All three primary confidence intervals include zero. The listed secondary outcome is the Psycho-motor Vigilance Test at the same time point. The adverse-event summary records zero serious events, zero other events, and zero deaths in each group.

The record notes six simulator failures that led to exclusion of those participants’ primary outcome data. It does not report the original sample-size justification, a detailed statistical analysis plan, multiplicity handling, or a full missing-data approach. Planning illustrations on the page are based on observed effects and should be distinguished from the trial’s original design assumptions.