Evidence-Based Practice: cram pack

Formula sheets, the key method steps for every topic and 8 practice problems, with full solutions at the back.

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1Formulas and methods

Evidence-based practice statistics

Sensitivity and specificity
Se = a/(a + c), Sp = d/(b + d)
Predictive values
PPV = a/(a + b), NPV = d/(c + d)
Accuracy
(a + d)/n
Likelihood ratios
LR+ = Se/(1 − Sp), LR− = (1 − Se)/Sp
PPV at prevalence p
Se·p / (Se·p + (1 − Sp)(1 − p))
Odds
odds = p/(1 − p); p = odds/(1 + odds); post-test odds = pre-test odds × LR
Risk measures
RR = EER/CER, ARR = CER − EER, RRR = ARR/CER
Number needed to treat
NNT = 1/ARR, rounded up; NNH = 1/(EER − CER)
Odds ratio
OR = ad/(bc)
Incidence rate
new cases / person-time

Method

  1. Draw the 2 × 2 table and label a, b, c and d before you calculate.
  2. Read sensitivity and specificity down the columns, predictive values along the rows.
  3. For another prevalence, imagine 10 000 people and fill the table with Se, Sp and the prevalence.
  4. For a likelihood ratio, convert the probability to odds, multiply, and convert back.
  5. For a trial, find EER and CER first; then RR = EER/CER, ARR = CER − EER and NNT = 1/ARR rounded up.

Descriptive statistics

Mean
x̄ = Σx/n
Sample standard deviation
s = √(Σ(x − x̄)²/(n − 1))
Median
middle value of the sorted data
z-score
z = (x − μ)/σ
Normal distribution
68% within ±1σ, 95% within ±2σ

Confidence intervals

σ known
x̄ ± z·σ/√n
σ unknown
x̄ ± t·s/√n, df = n − 1
Critical z
90%: 1.645, 95%: 1.96, 99%: 2.576
Sample size
n = (z·σ/E)², rounded up

Method

  1. Decide between z (population σ known) and t (only the sample s, with n − 1 degrees of freedom).
  2. Find the critical value for the confidence level.
  3. Margin of error: E = critical value × standard deviation/√n.
  4. Interval: x̄ ± E.

Hypothesis tests & confidence intervals

z-test for a mean
z = (x̄ − μ0)/(σ/√n)
t-test for a mean
t = (x̄ − μ0)/(s/√n), df = n − 1
Two-sided at 5%
reject H0 if |z| > 1.96
Confidence interval
x̄ ± z·σ/√n

Method

  1. State H₀ and H₁ and decide whether the test is one- or two-sided.
  2. Calculate the test statistic: (x̄ − μ₀)/(σ/√n), or with s and t.
  3. Compare with the critical value, or find the p-value.
  4. Reject H₀ if the statistic is beyond the critical value (p below α), and state the conclusion in words.

2Practice problems

1.Evidence-based practice statisticsMedium
casesperson-yearsexposed4556900not exposed11500

Practice exercise (made-up values, not clinical guidance). In a cohort study, exposed people contributed 6900 person-years with 455 new cases, and unexposed people 500 person-years with 11 new cases. Find the incidence rate ratio IRR (exposed versus unexposed). Round to two decimal places.

exposed: 455/6900 PYnot exposed: 11/500 PY
IRR =
2.Evidence-based practice statisticsHard
pre-test15%post-test?p′LR+

Practice exercise (made-up values, not clinical guidance). A patient has a pre-test probability of 15% for a disease. A test with sensitivity 80% and specificity 94% comes back positive. Find the post-test probability p′ of the disease as a percentage. Round to one decimal place.

pre-test 15%Se = 80%Sp = 94%positive
p′ = %
3.Descriptive statisticsMedium
10152025303540455055

Find the sample standard deviation s of the data: 39, 57, 57, 58, 56, 10.

n = 6
s =
4.Descriptive statisticsHard
z −2−1012

A quantity is normally distributed with mean 100 and standard deviation 15. What proportion P of values is above 77.5?

μ = 100σ = 15x = 77.5
P =
5.Confidence intervalsMedium
n = 13, s = 2.5LU = ?x̄ = 82E99%

A sample of 13 items has mean 82 and standard deviation s = 2.5. The population is roughly normal. Find the upper limit of the 99% confidence interval for the mean.

n = 13x̄ = 82s = 2.599%t(12) = 3.055
upper limit =
6.Confidence intervalsHard
μ₁ − μ₂, t(29) = 1.6990LU = ?x̄₁ − x̄₂E90%

Two fertilisers are tested. Plot group 1: 5 plots, mean yield 84.5 kg, standard deviation 9 kg. Plot group 2: 26 plots, mean 77 kg, standard deviation 6.5 kg. Assume equal variances (pooled t, df = n₁ + n₂ − 2). Find the upper limit of the 90% confidence interval for μ₁ − μ₂.

n₁ = 5x̄₁ = 84.5s₁ = 9n₂ = 26x̄₂ = 77s₂ = 6.590%t(29) = 1.699
upper limit = kg
7.Hypothesis tests & confidence intervalsMedium
−2.4472.447t = ?df = 6

7 employees take a typing test before and after a training course. For each person the difference d = after − before (words per minute) is recorded. The mean difference is −3.99 and the standard deviation of the differences is 8.8. Find the paired test statistic t for H₀: μd = 0.

n = 7d̄ = −3.99sd = 8.8
t =
8.Hypothesis tests & confidence intervalsHard
z −2.57602.576

A sample of 36 measurements has mean 201.5. The population standard deviation is 10. Find the lower limit L of the 99% confidence interval for the mean.

x̄ = 201.5σ = 10n = 3699%
L =

3Solutions

1.Evidence-based practice statistics

Answer: IRR = 3

Likelihood ratios and risk measures: LR+ = sensitivity/(1 − specificity), LR− = (1 − sensitivity)/specificity. In a trial, EER and CER are the event rates with and without treatment: RR = EER/CER, ARR = CER − EER, RRR = ARR/CER and NNT = 1/ARR, rounded up. In a case-control study only the odds ratio OR = ad/(bc) can be used. An incidence rate = new cases/person-time.

Incidence rates

exposed: 455/6900 = 65.94 per 1000 person-years
not exposed: 11/500 = 22 per 1000 person-years

Rate ratio

IRR = 65.94/22 = 2.997 ≈ 3

Answer

IRR = 3
2.Evidence-based practice statistics

Answer: p′ = 70.2 %

Predictive values depend on prevalence: PPV = Se·p/(Se·p + (1 − Sp)(1 − p)) and NPV = Sp(1 − p)/(Sp(1 − p) + (1 − Se)p). With likelihood ratios: pre-test odds = p/(1 − p), post-test odds = pre-test odds × LR, probability = odds/(1 + odds). For a population of N, true positives = N·p·Se and false positives = N·(1 − p)·(1 − Sp). NNT = 1/(CER × RRR), rounded up.

Likelihood ratio

LR+ = 0.8/(1 − 0.94) = 13.33

Pre-test odds

0.15/(1 − 0.15) = 0.1765

Post-test odds

0.1765·13.33 = 2.353

Post-test probability

p′ = 2.353/(1 + 2.353) = 0.7018 ≈ 70.2%

Answer

p′ = 70.2%
3.Descriptive statistics

Answer: s = 19.14

Descriptive statistics: the mean is the sum divided by n; the median is the middle value of the sorted data (the average of the two middle values when n is even). The sample standard deviation is s = √(Σ(x − x̄)²/(n − 1)). A z-score z = (x − μ)/σ says how many standard deviations a value lies from the mean.

Mean

x̄ = 277/6 = 46.17

Squared deviations

Σ(x − x̄)² = (−7.167)² + 10.83² + 10.83² + 11.83² + 9.833² + (−36.17)² = 1831

Standard deviation

s = √(1831/5) = 19.14

Answer

s = 19.14
4.Descriptive statistics

Answer: P = 0.9332

Descriptive statistics: the mean is the sum divided by n; the median is the middle value of the sorted data (the average of the two middle values when n is even). The sample standard deviation is s = √(Σ(x − x̄)²/(n − 1)). A z-score z = (x − μ)/σ says how many standard deviations a value lies from the mean.

Standardise

z = −1.5

Standard normal table

Φ(−1.5) = 0.06681
P = 1 − 0.06681 = 0.9332

Answer

P = 0.9332
5.Confidence intervals

Answer: upper limit = 84.12

Confidence interval for a mean: x̄ ± margin of error. With a known population σ the margin is z·σ/√n; with only the sample standard deviation s, use t with n − 1 degrees of freedom: t·s/√n. Critical values: z = 1.645 (90%), 1.96 (95%), 2.576 (99%). To get a margin E or smaller, you need n ≥ (z·σ/E)², rounded up.

Critical value

df = n − 1 = 12, t = 3.055

Margin of error

E = 3.055·2.5/√13 = 2.118

Interval

82 ± 2.118 → [79.88, 84.12]

Answer

upper limit = 84.12
6.Confidence intervals

Answer: upper limit = 13.22 kg

Interval for a difference: estimate ± critical value × standard error. For two independent means with known σ: SE = √(σ₁²/n₁ + σ₂²/n₂) and z. With equal unknown variances: pooled s_p and t with n₁ + n₂ − 2 degrees of freedom. For paired data, work with the differences: d̄ ± t·s_d/√n.

Pooled standard deviation

sp² = (4·9² + 25·6.5²)/29 = 47.59
sp = 6.899

Margin of error

E = 1.699·6.899·√(1/5 + 1/26) = 5.724

Interval

7.5 ± 5.724 → [1.776, 13.22]

Answer

upper limit = 13.22 kg
7.Hypothesis tests & confidence intervals

Answer: t = −1.2

Testing a mean: the test statistic measures how many standard errors the sample mean lies from the value claimed in H₀: z = (x̄ − μ₀)/(σ/√n) when σ is known, t = (x̄ − μ₀)/(s/√n) when it is estimated from the sample. A confidence interval is x̄ ± (critical value)·(standard error).

Standard error of the mean difference

SE = 8.8/√7 = 3.326

Test statistic

t = −3.99/3.326 = −1.2

Answer

t = −1.2

With df = 6, the two-sided 5% critical value is 2.447; |t| is smaller, so H₀ is not rejected.

8.Hypothesis tests & confidence intervals

Answer: L = 197.2

Testing a mean: the test statistic measures how many standard errors the sample mean lies from the value claimed in H₀: z = (x̄ − μ₀)/(σ/√n) when σ is known, t = (x̄ − μ₀)/(s/√n) when it is estimated from the sample. A confidence interval is x̄ ± (critical value)·(standard error).

Margin of error

E = 2.576·10/√36 = 4.293

Interval limit

L = 201.5 − 4.293 = 197.2

Answer

L = 197.2

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