Why Are Clinicians Not Embracing the Results fromPivotal Clinical Trials in Severe Sepsis? A BayesianAnalysis
1 Department of Internal Medicine, University of Nebraska Medical Center, Omaha, Nebraska, United States of America, 2 Assistant Professor, Department of Biostatistics,
College of Public Health, University of Nebraska, Omaha, Nebraska, United States of America
Background: Five pivotal clinical trials (Intensive Insulin Therapy; Recombinant Human Activated Protein C [rhAPC]; Low-Tidal Volume; Low-Dose Steroid; Early Goal-Directed Therapy [EGDT]) demonstrated mortality reduction in patients withsevere sepsis and expert guidelines have recommended them to clinical practice. Yet, the adoption of these therapiesremains low among clinicians.
Objectives: We selected these five trials and asked: Question 1-What is the current probability that the new therapy is notbetter than the standard of care in my patient with severe sepsis? Question 2-What is the current probability of reducing therelative risk of death (RRR) of my patient with severe sepsis by meaningful clinical thresholds (RRR .15%; .20%; .25%)?
Methods: Bayesian methodologies were applied to this study. Odds ratio (OR) was considered for Question 1, and RRR wasused for Question 2. We constructed prior distributions (enthusiastic; mild, moderate, and severe skeptic) based on variouseffective sample sizes of other relevant clinical trials (unfavorable evidence). Posterior distributions were calculated bycombining the prior distributions and the data from pivotal trials (favorable evidence).
Main Findings: Answer 1-The analysis based on mild skeptic prior shows beneficial results with the Intensive Insulin, rhAPC,and Low-Tidal Volume trials, but not with the Low-Dose Steroid and EGDT trials. All trials’ results become unacceptable bythe analyses using moderate or severe skeptic priors. Answer 2-If we aim for a RRR.15%, the mild skeptic analysis showsthat the current probability of reducing death by this clinical threshold is 88% for the Intensive Insulin, 62–65% for the Low-Tidal Volume, rhAPC, EGDT trials, and 17% for the Low-Dose Steroid trial. The moderate and severe skeptic analyses show noclinically meaningful reduction in the risk of death for all trials. If we aim for a RRR .20% or .25%, all probabilities ofbenefits become lower independent of the degree of skepticism.
Conclusions: Our clinical threshold analysis offers a new bedside tool to be directly applied to the care of patients withsevere sepsis. Our results demonstrate that the strength of evidence (statistical and clinical) is weak for all trials, particularlyfor the Low-Dose Steroid and EGDT trials. It is essential to replicate the results of each of these five clinical trials inconfirmatory studies if we want to provide patient care based on scientifically sound evidence.
Citation: Kalil AC, Sun J (2008) Why Are Clinicians Not Embracing the Results from Pivotal Clinical Trials in Severe Sepsis? A Bayesian Analysis. PLoS ONE 3(5):e2291. doi:10.1371/journal.pone.0002291
Editor: Adam J. Ratner, Columbia University, United States of America
Received October 26, 2007; Accepted April 9, 2008; Published May 28, 2008
Copyright: ß 2008 Kalil, Sun. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricteduse, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The authors have no support or funding to report.
Competing Interests: The authors have declared that no competing interests exist.
results and brought the prospect of improving the survival ofpatients with severe sepsis.
‘‘If we begin with certainties, we shall end in doubts; but if we begin
Ten multinational medical societies sponsored a joint statement,
with doubts, and are patient with them, we shall end with certainties.’’
‘Surviving Sepsis Campaign’, in which recommendations aremade to include the results of these trials in the standard of care for
patients with severe sepsis . These recommendations have also
More than 20 clinical trials involving over 10,000 patients have
been evaluated by the Joint Commission on Accreditation of
been performed in patients with sepsis and severe sepsis in the last
Healthcare Organizations . Despite these positive outcomes
15 years with little success in reducing mortality . More
and recommendations, scientists and clinicians have been either
recently, five published clinical trials: Early Goal-Directed
slow or resistant to adopt the results of these trials at face value in
Therapy , Recombinant Human Activated Protein C ,
order to apply them to patient care [9–25]. Still, strong
Low-Dose Steroid , Low-Tidal Volume-ARDS Network ,
endorsement by the medical societies is not coming without
and Intensive Insulin Therapy  demonstrated positive outcome
criticisms and opposition by the medical community [8,26]. Why
is this resistance to accept statistically significant results from large
probability of having a disease based on tests results without
clinical trials so accentuated in the sepsis field?
specifying the disease’s prevalence’’ . The basic idea described
We propose that the genesis for most of these issues lies in the
by Bayes demonstrates that the product between the prior
confounding interpretation and poor translation of these results to
probability and the evidence provided by the new trial (also called
the bedside, and the lack of formal analysis combining previous
Bayes factor) will give us the posterior probability, which we call
evidence and the current positive clinical trials. While controversy
the ‘‘current probability’’ in our paper. This simple and clever
is necessary for the progression of science , when it comes to
algebraic calculation allows us to overcome the unsolvable ‘long
treating a patient with severe sepsis, a clinical decision is also
term hypothetical repetitions’ inherent issue of the classic method.
necessary for the betterment of this patient’s outcome.
At the same time, it gives us what we are mostly looking for in our
In the following paragraphs, we argue that the best solution for
daily medical practice, i.e. what is the current probability to
the understanding of pivotal clinical trials in severe sepsis can only
achieve the results of this pivotal trial in my patients? The potential
come from a friendly reunion of classic (frequentist) and Bayesian
‘‘subjectivity’’ of these priors have made some statisticians and
statistical methodologies [28–31]. The application of this more
clinicians concerned about the use of this method. However, the
inclusive and robust interpretation of trial results will facilitate
complete exclusion of prior knowledge and evidence from the
their application directly to the bedside, and will hopefully further
design and interpretation of recently completed clinical trials has
improve the care of our patients with severe sepsis. Moreover, this
been compared to a sentencing judge who overlooks the prior
‘‘dualistic’’ approach will also empower us to better define the
convictions of a habitual criminal . Needless to say, the
need for confirmatory trials in order to optimize the current
commonly used classic methodology in current clinical trials is far
from objective. For example, the models assumed, the parametersand hypothesis chosen, and the experimental designs employed
 are typical features that incorporate much subjectivity intothe classic analysis. We agree with Berry  that ‘‘…silent
subjectivities such as these (seen with classic methods) are
The ‘‘early goal-directed therapy’’ (EGDT) trial  will be used
dangerous in that they are difficult or impossible to make explicit.
as a practical example to describe the rationale for our
By contrast, subjectivity in prior distributions (as seen with
methodology. This trial aimed to compare the use of early volume
Bayesian methods) is explicit and open to examination-and
replacement/vasopressor use in the treatment arm against
critique-by all’’. Thus, how should we best determine the priors
standard of care in the control arm for patients with severe sepsis.
for this study? This so-called subjectivity is easily resolved in the
The final results showed a 42% relative reduction in the risk of
severe sepsis world because we have many negative clinical trials
death (16% absolute risk reduction) of in-hospital mortality with a
done before the current positive trials, which set the stage for the
95% confidence interval (CI) (0.13–0.62), p = 0.009. Common
perfect use of Bayesian methodology. We will provide the clinician
clinical interpretations are: (a) there is only a 0.9% probability of a
with a realistic spectrum of prior distributions, so he/she can find
false positive result (rejecting the null hypothesis when there is no
the current probability of the new treatment being no better than
treatment difference); (b) there is a 95% probability of the true risk
the control (standard of care), and the current probability of
ratio being somewhere between 0.13 and 0.62 (a reduction of 13–
reducing mortality by a clinically meaningful threshold. These two
62% in the relative risk of death). These interpretations are
probabilities will allow the clinician to make the best clinical
incorrect due to the misunderstanding of the classic or frequentist
decision for the patient with severe sepsis without being entirely
(frequency based view of probability) statistical reporting used in
dependent on sponsors, regulators, editors, and experts in the field.
this and most trials [32–35]. The correct interpretation of theclassic method for this trial is the following: There is a 0.9%
probability that results as good as or better than the ones found in
1. What is the current probability that the new therapy is
this trial (42% relative reduction in the risk of death), will be
not better than the standard of care in my patient with
observed among a large number of hypothetical repetitions of this
The goal of the first part of our study is to assess
trial under the null hypothesis of no treatment effect. In addition,
the current probability that the new therapy is no better than the
the CIs generated from 95% of these hypothetical trials will cover
control, i.e. standard of care. We used the log-odds ratio (ln(OR))
the true mortality reduction. This rather convoluted language is
of death for the new treatment group compared to the control
the only possible interpretation which explicitly states that the
group. We considered the new therapy to be no better than the
classic method cannot provide the probabilities that clinicians are
control if the ln(OR) was found to be greater than 20.05 [38,39].
seeking for. In other words, clinicians are interpreting the
We then constructed various prior distributions of ln(OR)
conventional p values and CIs as ‘current probabilities’, although
assuming previous trials of different effective sample sizes (see
the classic method alone only provides us with probabilities over a
Appendix S1). The prior distributions may be based on the
large number of hypothetical repetitions in the long term.
following information: Early Goal-Directed Therapy [40–47],
Here is where the Bayesian methodology comes in to
rhAPC [48–53], Low-Dose Steroids [54–67], Low-Tidal Volume
complement the classic interpretation of clinical trials. It allows
[68–74], Intensive Insulin Therapy [75–85]. Of note, some trials
us to think the way most clinicians are already thinking ! That
were performed before and others after the pivotal positive trial of
is, what is the posterior or ‘current probability’ (not the probability
a given therapy. This inclusive approach of all evidence available
in the long term of hypothetical trial repetitions) of observing this
is an important strength of the Bayesian technique, which does not
outcome in a given trial or population.
require that the priors have a temporal order [32,37,86,87]. This
In order to use the Bayesian methodology, a prior probability is
list of studies for each therapy allows the reader to get his/her own
required. The prior probability can be based on all available
effective sample size by summing up the prior unfavorable
evidence (i.e. biological rationale and its pre-clinical evaluation;
evidence (total sample size of relevant negative clinical trials). If
observational and experimental clinical data) gathered by studies
believing there is no relevant previous negative data, one can
other than the new trial being currently analyzed. An analogy to
assume the effective sample size to be 1 . This gives us the non-
the diagnostic setting states that ‘‘it is not possible to find a
informative prior, which is our ‘enthusiastic’ prior, since it is
Table 1. Current probability of new treatment being no better than control based on mortality outcomes.
Sample Size of Unfavorable Evidence (Bayesian Priors) CURRENT PROBABILITY OF NEW TREATMENT BEING NO BETTER THAN CONTROL
MILD-MODERATE SKEPTIC (Sample Size = 500)
ignoring all negative sepsis trials already published. If one is
publication (42%). This level of prediction can not be achieved
skeptical about the effects of the new therapy based on previous
phase 2 and 3 trials, observational studies, or clinical experience,
The results of the five positive clinical trials [2–6] will be
the effective sample size of negative evidence for the (skeptical)
discussed in the context of the two probability questions described
prior will be larger. Thus, the more skeptical one is based on the
above. Because of the non-significant overall results of the low-
prior information, the harder it is to conclude efficacy using the
steroid trial for mortality , we will evaluate the prospectively
same pivotal trial data. Based on the mortality rate and the
defined ‘‘non-responders’’ sub-population. Due to the low overall
required sample size to evaluate new therapies for severe sepsis in
control mortality (8%), and the inclusion of all comers (with and
current times, the following effective sample sizes of negative
without severe sepsis) to a surgical ICU in the intensive insulin trial
evidence were analyzed for each new therapy: Enthusiastic (n = 1);
, we will evaluate the prospectively defined ‘‘.5 days in ICU’’
Mildly skeptic (n = 200); Mild-moderately skeptic (n = 500);
sub-population. This subgroup control had mortality rates (20%)
Moderately skeptic (n = 1,000); Severely skeptic (n = 2,000). We
closer to those of the other trials. The rhAPC trial  will have two
consider the current probability of ln(OR) .20.05 being less than
analyses, since the drug was FDA approved based on the sicker
0.05 as sufficient evidence to conclude that the new treatment is
(APACHE II .25) sub-population. Even though the ARDSNet
better than the control. For example, if the clinician sums up
Low-Tidal Volume trial  was not specifically designed for
approximately 500 subjects from 3 previous negative trials on low-
patients with severe sepsis, we included it because approximately
tidal volume therapy [69–71] (i.e. mild to moderate skeptic about
60% of the trial population had sepsis or pneumonia, and the trial
this therapy), our analysis (table 1) will provide a 0.05 current
results have been recommended for patients with severe sepsis by
probability of low-tidal volume therapy being no better than
control. As the reader can appreciate in table 1, because of thenegative prior information that needs to be overcome, this current
probability (0.05) is different from the classic p value reported inthe original trial publication (p = 0.007).
1. What is the current probability that the new therapy is
2. What is the current probability of decreasing the
not better than the standard of care in my patient with
relative risk of death of my patient with severe sepsis by a
Table 1 shows the current probability of the new treatment
clinical trials already published , the recent FDA approval of a
being no better than the control. If we are enthusiastic about the
new therapy on sepsis , and a 28-day mortality ranging from
five trials, all probabilities are small. If we are just mildly skeptic,
30–40%, no new therapy for severe sepsis will likely be acceptedby clinicians or regulators if the relative risk reduction (RRR) formortality is not greater than 15–25% (absolute risk reduction
Table 2. Probability of Relative Risk Reduction (RRR) of
(ARR) $5–10%). For example, a trial with a control arm mortality
of 30% and a experimental arm mortality of 25% would result inan ARR = 5% and a RRR = 16%. Thus, we will present the
current probabilities for greater than 15%, 20%, and 25% RRRfor mortality in each trial (see Appendix S1). This second analysis
can be thought of as analogous to ‘clinical significance’. For
example, if the clinician sums up approximately 1000 subjects
from 2 previous negative trials on volume replacement/vasopressor use [45,46] (i.e. moderate skeptic about this therapy)
and believes that a minimum of 15% RRR needs to be
demonstrated to add the EGDT to standard of care of patients
with severe sepsis, our analysis (table 2) will provide a 6% current
probability of reaching at least this RRR in mortality. This current
probability (6%) of reducing mortality by at least 15% is differentfrom the classic overall RRR reported in the original trial
the probabilities from the EGDT  and Low-Dose Steroid 
Table 3. Probability of Relative Risk Reduction (RRR) of
trials become 0.05 or larger, which may not provide strong enough
evidence to change the standard of care. If we take into accountthe preceding multitude of unfavorable trials and analyze theseresults in the light of a mild-moderate skeptical view, the current
probabilities for these two trials rise to 0.14 and 0.21, respectively. The results of rhAPC, Low-Tidal Volume, and Intensive Insulin
trials remain acceptable if we assume a mild skepticism-all withcurrent probabilities of less than 0.05. The mild-moderate skeptic
analysis makes both the Low-Tidal Volume and Intensive Insulin
results reach the 0.05 probability of the new treatment being no
better than the control, and the moderate skeptic analysis showsthe rhAPC trial with the same 0.05 probability as well. The rhAPC
APACHE II sub-analysis shows probabilities below 0.05 in all
prior levels except in the severe skeptic analysis. If the clinician is
severely skeptical, no trial results will lead to changes in thestandard of care.
2. What is the current probability of decreasing the
relative risk of death of my patient with severe sepsis by
Table 2 illustrates the current probabilities of achieving at least a
specific clinically meaningful RRR based on the chosen cut-off andprior distribution. For a clinician who is enthusiastic (i.e. choosing
the enthusiastic prior) about EGDT and believes that an RRR
should not be less than 20% to use this new therapy in patient care,
the chance of EGDT to decrease the relative risk of death more than20% is 87%. If RRR.15% is the goal, this therapy will have a 94%
(enthusiastic) and 62% (mildly skeptic) current probabilities. This is atangible and easy result to translate and apply to bedside. For the
mildly skeptic requiring a RRR.20% the probability drops to
clinician who is mildly skeptical about this therapy, the chance of
37%, and for the mild-moderate skeptic requiring any RRR, the
EGDT to decrease the relative risk of death more than 20% in a
probabilities of benefit from this therapy remain all below 40%.
given patient will decrease to 41%, which may be too low for general
The Intensive Insulin trial (table 6) shows consistent probabil-
clinical application. If a moderately skeptical prior is applied to this
ities of reducing the risk of death (69–98%) for all RRR levels in
trial, the probability of having a RRR greater than 15% and 20%
both enthusiastic and mild skeptic analyses. The probability
drops substantially to 6% and 1%, respectively.
remains above 60% even in the mild-moderate skeptic analysis if
For the rhAPC overall results (table 3), in the best case scenario
the aim is a RRR.15%. However, for the moderate or severe
(enthusiastic), the current probability of reaching a 20% RRR in
skeptic approach, all results are below 42%.
mortality is 43%. If the clinician is comfortable with a 15% RRR,then the probability of reaching this cut-off with rhAPC goes up to
75% for the enthusiastic, and to 65% for the mildly skeptical, butremains low at 30% for the moderately skeptical. On the other
The first analysis indicates that there is sufficient evidence to
side, if we analyze this trial based on APACHE II .25 subgroup
support the efficacy in all five trials only if we are enthusiastic with
and enthusiastic prior, then there is 97%, 90%, and 72%
respect to the prior distribution of each of these therapies. If we
probability of respectively reaching RRR of 15%, 20%, and
analyze them with the mild skepticism, only the Intensive Insulin,
25% with rhAPC. These are more optimistic results than the
rhAPC, and Low-Tidal Volume trials show beneficial results.
overall trial analysis, but if the clinician remains a mild-moderateskeptic, the probability of achieving any of those same RRR
Table 4. Probability of Relative Risk Reduction (RRR) of
thresholds becomes smaller; 63%, 30%, and 7%, respectively. The
moderate and severe skeptic analyses show most probabilities ofreaching any meaningful RRR in the single digits.
The Low-Dose Steroid trial analysis demonstrates well the
importance of this type of clinical threshold analysis. In the bestcase-scenario for the least meaningful RRR (15%), the enthusiastic
approach shows a current probability of 58% (table 4). Even for
the mildly skeptic, steroids have an unacceptably low current
probability (20% or less) of reaching any meaningful RRR in
mortality. We also performed an additional analysis about theprobability of steroids reaching a RRR.10%, but except for the
enthusiastic prior (76%), all other probabilities remain similarly
The Low-Tidal Volume trial (table 5) shows a current
probability of 83% (enthusiastic) or 65% (mild skeptic) for thephysician who is looking for a RRR.15%. However, for the
than 20%. On the other hand, if we are mildly skeptical and aim a
Table 5. Probability of Relative Risk Reduction (RRR) of
RRR.15%, the probability of reducing the risk of death is 88%
for the Intensive Insulin trial, 62–65% for the rhAPC, Low-TidalVolume, and EGDT trials, and just 17% for the Low-Dose Steroidtrial. Unless we are less ambitious with respect to the RRR, i.e.
15%, and accept an enthusiastic to mildly skeptic prior, none of
these trials have shown strong enough evidence for diminishing the
risk of death in patients with severe sepsis. Of note, the consistently
very low current probabilities (poor strength of evidence) ofobserving mortality reduction with Low-Dose Steroids in both of
our analyses (questions 1 and 2) was just confirmed by a recently
published phase III trial . Interestingly, our statistical analysis
predicting the poor results of Low-Dose Steroids was completed
and submitted long before the report of this new phase III trial.
We would like to recognize some limitations of our study. The
statistical approach we used for this study may appear to produce
more conservative results than conventional methods, but this is,in fact, the main strength of our data. The Bayes’ theorem is
Although the rhAPC APACHE II .25 sub-analysis remains
uncontroversial if derived from known data . We strongly
beneficial in the moderate skeptic analysis, the original results have
believe that the prior negative evidence is so abundant that we
not been validated in a prospective phase III trial yet. Based on
have the ethical obligation to consider and use this methodology in
our current results indicating high probability of new treatment
the analysis of any new therapy for severe sepsis. The different
being no better than controls in all skeptic analyses for the EGDP
sample sizes of each trial may have influenced the current
and Low-Dose Steroid trials, as well as on the numerous
probabilities of our first analysis, but the consistent results found in
unfavorable trials evaluating different regimens of volume
both first and second analyses make the sample size influence less
replacement/vasopressors or steroids in severe sepsis, we demon-
likely. Also, because some of the therapeutic interventions were
strate that the beneficial results from these two trials are the ones
not identical within a specific class, and other studies were different
with the weakest strength of evidence. All five trials become
with respect to their trial design, we advise the reader to carefully
unacceptable if we are moderately or severely skeptical, because
evaluate the most appropriate priors to avoid overt pessimistic or
the current probability of the new therapy being no better than the
control is too high for general clinical application. The fact that
In conclusion, our study provides four clinical and research
most overall beneficial results are not even that impressive with the
lessons with profound implications to the care of our patients with
mild-moderately skeptic analysis is concerning.
The second analysis based on a specific clinical cut-off of the
RRR brings important light to the interpretation of these trials.
Assuming an enthusiastic prior, the Intensive Insulin, the rhAPC
Our results unambiguously demonstrate that it is important to
APACHE II .25, and the EGDP trials demonstrate the highest
replicate the results of each of these trials in well designed
probability (87–96%) of reaching an RRR of at least 20% for
confirmatory studies if we want to provide patient care based on
mortality. However, the absence of a majority of patients with
scientifically sound evidence. Further, the many study design issues
severe sepsis in the Intensive Insulin trial, the absence of
raised, e.g. standard of care of control groups (EGDT and Low-
prospective validation of the rhAPC APACHE II .25 subgroup
Tidal Volume trials [10–12,17,21–24]; the rhAPC APACHE II
population, and the weak strength of evidence from our first
.25 subgroup analysis without prospective validation  and the
analysis for the EGDP trial, all suggest that more skepticism should
poor results of this subgroup in the ADDRESS trial [49,89]; the
be taken before assuming these probabilities of RRR.20%. In
controversial definitions of adrenal insufficiency [20,90,91], and
this case, the moderate skeptic analysis for these 3 trials shows all
the just reported Low-Dose Steroid phase III trial with negative
current probabilities of 23% or less of reducing death risk by more
results ; and the failure of the Intensive Insulin Therapy toimprove survival in the medical ICU population  allcorroborate our conclusion for lesson 1.
Table 6. Probability of Relative Risk Reduction (RRR) ofMortality by Intensive Insulin Therapy.
Lesson 2–Standard of care for patients with severe sepsis
The strength of evidence (statistical and clinical) is overall weak
for the five trials. These results make any legitimate changes in the
standard of care a very difficult task to accomplish. While we
endorse the genuine need for more evidence, we are aware of the
urgent need to improve the survival outcome of our patients with
severe sepsis. How to reconcile this apparent conundrum? SirAustin Hill already had the answer in his seminal paper from
1965: ‘‘All scientific work is incomplete–whether it be observa-
tional or experimental. All scientific work is liable to be upset or
modified by advancing knowledge. That does not confer on us a
freedom to ignore the knowledge that we already have, or topostpone the action that it appears to demand at a given time’’
. Before we have the results of confirmatory trials, we urge
clinicians to use our clinical threshold analysis of RRR for
mortality from each trial (tables 2–6) to guide the best course of
We anticipate that our comprehensive analysis and interpreta-
action to take for their patients with severe sepsis.
tion of these trials will bestow realistic and practical tools toclinicians to decide on their own and without undue influence how
Lesson 3–No need for changes in the measurement of
to best apply the results of these trials to their patients with severe
The most important premise to change the measurement of
quality of care must be based on strong and established scientific
evidence, but this is lacking at this time. When we completed our
study it became obvious that, with such low strength of evidence
Found at: doi:10.1371/journal.pone.0002291.s001 (0.05 MB
and critical need for confirmatory trials, none of these studies’results should be applied as rigid tools to measure quality of care in
patients with severe sepsis in the ICU.
Lesson 4–Need for both classic and Bayesian
The authors thank Ms Elaine Litton for providing outstanding adminis-
As we demonstrate in this paper, the dual use of these methods
is powerful and synergistic to accomplish an ample interpretation
of these pivotal trials. We strongly suggest that trialists, sponsors,
Conceived and designed the experiments: AK JS. Performed the
regulators, and journal editors become more proactive with
experiments: AK JS. Analyzed the data: AK JS. Wrote the paper: AK
respect to the use of this dual statistical approach. Patients will be
the ultimate beneficiaries from this more encompassing strategy.
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Address by the Chief Executive Officer of the National Heritage Council Adv. Sonwabile Mancotywa at the Graduation CeremonyFort Hare University – AliceMay 12, 2011 Introduction My invitation here requested that I address myself on the subject of social cohesion and its relationship to heritage. Iguess the Office of the Vice-Chancellor would like me to answer the question: How do we harness
MPH5041, 2013 Biostatistics for Clinical and Public Health Research Test 3, Due April 26, 2013 by 11:59pm Modules Covered: This Test covers Modules 1-5. All questions must be answered using statistical knowledge in Modules 1-5 only. SPSS or any other statistical package can be used for data analysis . Assignment General Instructions: This test is wort