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Table 3 Assessment of unmeasured confounding among meta-analyses assessed by Point Estimate and PMSE sensitivity analyses

From: How likely is unmeasured confounding to explain meta-analysis-derived associations between alcohol, other substances, and mood-related conditions with HIV risk behaviors?

Exposure

Outcome

Pooled RR

(95% CI)1

E-value2

(95% CI LL)

Bias factor3

Bias-adjusted RR (95% CI)

p̂(q)4

\({\rm{\hat T}}\)(r, q)5

Ĝ(r, q)6

Opioids

Non-adherence

1.28 (1.16–1.42)

1.88 (1.60)

1.11

1.15 (1.05–1.28)

0.702

1.254

1.819

Alcohol

Unprotected sex

1.36 (1.26–1.46)

2.05 (1.83)

1.17

1.16 (1.07–1.25)

0.67

1.452

2.263

Tobacco

Unprotected sex

1.24 (1.12–1.37)

1.79 (1.48)

1.17

1.06 (0.96–1.17)

0.429

1.469

2.299

Opioids

Unprotected sex

1.10 (0.89–1.37)

1.44 (1.00)

1.17

0.94 (0.76–1.17)

0.315

1.315

1.959

Stimulants

Unprotected sex

1.44 (1.37–1.52)

2.24 (2.08)

1.17

1.23 (1.17–1.30)

0.786

1.569

2.514

Depression

Unprotected sex

1.24 (1.10–1.41)

1.80 (1.44)

1.01

1.23 (1.10–1.40)

0.769

1.279

1.875

Anxiety

Unprotected sex

1.19 (1.08–1.32)

1.67 (1.38)

1.01

1.18 (1.07–1.30)

0.688

1.294

1.912

Tobacco

Transactional sex

1.75 (1.32–2.3)

2.89 (1.98)

1.17

1.49 (1.13–1.97)

0.791

2.190

3.805

Opioids

Transactional sex

1.39 (1.1–1.76)

2.12 (1.43)

1.17

1.18 (0.94–1.51)

0.588

1.691

2.773

Alcohol

Multiple sexual partners

1.40 (1.27–1.53)

2.14 (1.86)

1.17

1.19 (1.09–1.31)

0.748

1.415

2.181

Stimulants

Multiple sexual partners

1.64 (1.43–1.89)

2.66 (2.21)

1.17

1.40 (1.22–1.61)

0.831

2.062

3.541

Depression

Multiple sexual partners

1.18 (1.07–1.31)

1.65 (1.34)

1.01

1.17 (1.06–1.30)

0.628

1.359

2.057

  1. 1 Converted from pooled ORs of Fig. 3
  2. 2 E-value: quantifies how strongly an unmeasured confounder would need to be associated with the exposure (minimum risk ratio RRXU) and outcome (minimum risk ratio RRUY) to fully explain the observed association (RRXY)
  3. 3 Bias factor: quantifies the maximum amount by which an unmeasured confounder could alter RRTXY
  4. 4 \({\rm{\hat p}}\)(q): the proportion of studies in a meta-analysis likely to meet or exceed a user-specified threshold of meaningfully strong effect (q)
  5. 5 \({\rm{\hat T}}\)(r, q): the minimum bias capable of reducing \({\rm{\hat p}}\)(q) to less than r (analogous to the bias factor)
  6. 6 \({\rm{\hat G}}\)(r, q): the minimum values of RRUY and RRXU capable of reducing p\({\rm{\hat p}}\)(q) to less than r (analogous to the E-value)