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Research > Hypothesis, levels of evidence, > Flashcards

Hypothesis, levels of evidence, Flashcards

1
Q

hypothesis

A
  • a tentative statement to explain certain observations or facts that requires further experimentation to be verified
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2
Q

alternate hypothesis

A
  • also known as the experimental hypothesis, the alternate hypothesis is a statement that the population parameter has a value that differs from the null hypothesis
  • in hypothesis testing, the alternate hypothesis is accepted when the null hypothesis is rejected
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3
Q

null hypothesis

A
  • also known as the statistical hypothesis, the null hypothesis is a statement that the values of a population parameter is equal to some claimed value
  • tested statistically by inferential statistics.
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4
Q

independent variables

A
  • the variable that is presumed to have caused or influenced the dependent variable. in research, the independent variable is what is controlled or manipulated by the researchers
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5
Q

dependent variables

A
  • the response or outcome assumed to be caused by the effect of the independent variable
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6
Q

p-value

A

the probability that a particular statistical result could have happened by chance

  • when the p-value is smaller than the stated value of alpha, or level of significance, the null is rejected
  • when the p-value is larger than the stated value of alpha or level of significance, the null hypothesis is not rejected
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7
Q

alpha level

A

also known as the significance level, the probability of rejecting the null hypothesis when it is true, or the chance of committing a Type I error
-traditio0nal values for alpha are 0.05 and 0.01

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8
Q

type I error

A
  • alpha error
  • the error the researcher makes when wrongly deciding to reject the null hypothesis, concluding that there is a different when there is not
  • false positive
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9
Q

type II error

A
  • beta error
  • the error the researcher makes when wrongly deciding not to reject the null hypothesis, concluding that there is no difference or relationship when there is. A type II error is a false negative findings
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10
Q

statistically significant

A
  • a statistical conclusion made when the probability is small that the difference between groups or the relationship between variables happened by chance
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11
Q

statistical power

A

-refers to the chance that a statistical test will lead to rejection of a false null hypothesis

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12
Q

effect size

A
  • a measure of the magnitude of the difference between two tx or the magnitude of the relationship between two variables
  • the larger the ES, the more likely it will be statistically significant
  • ES is one of the statistical elements used to estimate sample size and perform a power analysis
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13
Q

effect size index

A
  • a statistic that represents effect size using a standardized value
  • generally, the effect size index is calculated by taking the difference between the two groups and dividing it by the SD of one of the groups
<0.1= trivial effect
0.1-0.3 = smaLL effect
0.3-0.5 = moderate effect
>0.5 = large effect
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14
Q

MCID

A

the smallest difference in a pt’s condition that the pt or clinician considers worthwile and that would, in the absence of side effects and excessive cost warrant a change in the pt’s management

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15
Q

MDD

A

the minimum detectable change in a patient’s condition beyond the threshold or measurement error

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16
Q

parameter

A
  • a numerical measurement describing some characteristic of a population
  • parameters are rarely known and usually estimated by statistics computed from a sample
17
Q

systematic review

A
  • a comprehensive review of the medical literature that uses explicit methods to systematically search, identify, appraise, and summarize all literature on a specific issue
  • for example, a Cochrane systematic review is a type of review aimed at providing evidence specifically in health care and health policy
18
Q

meta-analysis

A
  • a systematic review that uses a statistical technique to derive an estimate of effect size cy combining the results of several randomized controlled trials to determine the overall effectiveness of a tx. this strategy can minimize the problem of small sample size from individual studies since the pooling of trials increases the overall sample size
19
Q

RCT

A
  • a form of experimental research used to assess the relative effect of a specific intervention compared to a control condition
  • pts are randomized into a control group and at least one experimental group
  • the control group receives either no tx or a standard default tx
  • ideally the groups will be identical except for the intervention they have been randomized to receive
  • random assignment reduces the risk of bias and increases the probability that differences between the groups can attributed to the intervention
20
Q

cohort study

A
  • longitudinal observational study in which individuals with a risk factor or exposure are followed over time to compare the occurrence of a disease in the exposed group to that of the group of unexposed individuals
  • the measure of association between exposure and disease in cohort studies is the relative risk
  • cohort studies can be performed prospectively or retrospectively from historical records
  • limitations of cohort studies include the excessive length of time a study can take and the influence of other lifestyle variables that invariably result in the two groups being uniquely different
21
Q

case control study

A
  • a type of retrospective, observational study in which individuals who already have a particular disease are matched with a comparison group of individuals without the disease
  • the history of exposure or other characteristics prior to the onset of the disease is recorded through interview and other sources and compared between the two groups
22
Q

cross-sectional study

A
  • a type or observational study where the data or observations are made at only one point in time and all subjects are tested at relatively the same time
  • a cross-sectional study aims to describe relationship between a disease or condition and factors of interest that exist in a specified population at a given time
  • these studies can describe the prevalence of disease or conditions and demonstrate associations, but they cannot distinguish between newly occurring and long-established conditions, nor can they identify casual relationships about what may have precipitated the disease or condition
23
Q

case report

A

is an in-depth description of an individual’s condition or response to tx

  • a case series consists of a collection of observations of similar cases
  • case reports may be used to generate theories and hypotheses for future research
  • they cannot test hypotheses or establish cause-and -effect relationships

Research (5 decks)

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