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In a 2018 study, researchers investigated the effect of the drug alteplase in the treatment of stroke patients (Thomalla et al. 2018). Patients were randomly assigned to receive intravenous alteplase or a placebo. The patients' neurological function was assessed 90 days after treatment. Of the 246 patients who received alteplase, 131 had a positive neurological outcome. Of the 244 patients who received a placebo, 102 had a positive neurological outcome. a. Was this an observational study or a controlled experiment? Explain. b. Find the percentage in each group that had a positive neurological outcome 90 days after treatment. c. Researchers performed a test to determine if there was a significant difference in the proportion of positive neurological outcomes between the treatment and control groups. The p-value for the test is \(0.003 .\) Based on a \(0.05\) significance level, choose the correct conclusion: i. Researchers have shown that alteplase may be an effective treatment for stroke patients. ii. Researchers have not shown that alteplase may be an effective treatment for stroke patients.

Step by step solution

01

Identifying the type of study

Observe the way the experiment was conducted. If the researchers randomly assigned the patients into two groups, one receiving the actual drug and the other receiving a placebo, this indicates a controlled experiment. Hence, this was a controlled experiment.

02

Computing the Percentage of Positive Outcomes

Find the ratio of positive outcomes to the total number of patients for both groups. Multiply by 100 to represent as a percentage. For the group that received alteplase, \(\frac{131}{246} * 100 \approx 53.25 \% \). For the group that received the placebo, \(\frac{102}{244}* 100 \approx 41.8 \% \) .

03

Interpreting the P-Value

A P-value is the probability that the results of another experiment of the same size and structure will deviate as much or more from the expected results if the null hypothesis were true. A P-value less than 0.05 (or whatever our alpha, the significance level, is set to) means the null hypothesis is rejected, indicating the difference seen is statistically different. The P-value 0.003 is less than 0.05, hence it indicates that the difference in the outcome for the group that received alteplase and the one that received a placebo is significant. Therefore, the researchers have shown that alteplase may be an effective treatment for stroke patients.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Random Assignment

In scientific research, random assignment is a vital aspect of controlled experiments. It involves randomly distributing participants into different groups to ensure each group is comparable. This process helps eliminate bias and guarantees that any differences between groups are due to the treatment being tested, rather than pre-existing differences. In the alteplase study, patients were randomly assigned to either receive the drug or a placebo.
This randomization ensures that personal variables, like age or severity of the stroke, do not skew the results.

• Increases the reliability of the results.
• Promotes balanced groups by chance.
• Ensures that differences in outcomes are attributed to the treatment.

By using random assignment, researchers can confidently use statistical methods to evaluate treatment effectiveness without being concerned about extraneous variables affecting the outcome.

Statistical Significance

Statistical significance helps us understand if the results from an experiment are likely due to the treatment or just random chance. It boils down to a threshold set by researchers (often 0.05) to determine the likelihood of errors in the conclusions. In this context, the significance level helps decide if alteplase truly impacts neurological outcomes for stroke patients.
If the p-value from the experiment is below the threshold, the results are deemed statistically significant. This means it's unlikely the observed difference between groups occurred just by chance. Thus, it supports the notion that the treatment (alteplase) made a real impact.

• Provides confidence in research findings.
• Helps inform decision-making in clinical settings.
• Assists in distinguishing between effective and ineffective treatments.

Statistical significance, in the alteplase study, allowed researchers to conclude with high confidence that the drug may be beneficial.

P-Value Analysis

The p-value is a statistical measure used to assess the evidence against the null hypothesis. It indicates the probability of obtaining results as extreme as those observed, given that the null hypothesis is true. In simpler terms, it tells us how likely our findings are due to randomness.
In the alteplase study, the p-value was 0.003, which is far below the common significance level of 0.05. A low p-value, like 0.003, suggests that the observed effect is strong and unlikely caused by random fluctuation. It allows researchers to reject the null hypothesis that there is no difference in treatment outcomes between the groups.

• Quantifies the strength of the evidence against the null hypothesis.
• Helps defend or refute the research hypothesis.
• Aids in confirming the effectiveness of a treatment.

P-value analysis is critical for drawing conclusions in studies, ensuring the results are not dismissed as mere coincidences.