metabin                 package:meta                 R Documentation

_M_e_t_a-_a_n_a_l_y_s_i_s _o_f _b_i_n_a_r_y _o_u_t_c_o_m_e _d_a_t_a

_D_e_s_c_r_i_p_t_i_o_n:

     Calculation of fixed and random effects estimates (relative risk,
     odds ratio or risk difference) for meta-analyses with binary
     outcome data. Mantel-Haenszel, inverse variance and Peto method
     are available for pooling.

_U_s_a_g_e:

     metabin(event.e, n.e, event.c, n.c, studlab,
             data = NULL, subset = NULL, method = "MH",
             sm = ifelse(!is.na(charmatch(method, c("Peto", "peto"), nomatch = NA)), "OR", "RR"),
             incr = 0.5, allincr = FALSE, addincr = FALSE, allstudies = FALSE,
             MH.exact = FALSE, RR.cochrane = FALSE, warn = TRUE)

_A_r_g_u_m_e_n_t_s:

 event.e: Number of events in experimental group.

     n.e: Number of observations in experimental group.

 event.c: Number of events in control group.

     n.c: Number of observations in control group.

 studlab: An optional vector with study labels.

    data: An optional data frame containing the study information,
          i.e., event.e, n.e, event.c, and n.c.

  subset: An optional vector specifying a subset of studies to be used.

  method: A character string indicating which method is to be used for
          pooling of studies. One of '"Inverse"', '"MH"', or '"Peto"',
          can be abbreviated.

      sm: A character string indicating which summary measure ('"RD"',
          '"RR"', or '"OR"') is to be used for pooling of studies.

    incr: Numerical value added to each cell frequency for studies with
          a zero cell count.

 allincr: A logical indicating if 'incr' is added to each cell
          frequency of all studies if at least one study has a zero
          cell count. If false, 'incr' is added only to each cell
          frequency of studies with a zero cell count.

 addincr: A logical indicating if 'incr' is added to each cell
          frequency of all studies irrespective of zero cell counts.

allstudies: A logical indicating if studies with zero or all events in
          both groups are to be included in the meta-analysis (applies
          only if sm = '"RR"' or '"OR"').

MH.exact: A logical indicating if 'incr' is not to be added to all cell
          frequencies for studies with a zero cell count to calculate
          the pooled estimate based on the Mantel-Haenszel method.

RR.cochrane: A logical indicating if 2*'incr' instead of 1*'incr' is to
          be added to 'n.e' and 'n.c' in the calculation of the
          relative risk (i.e., 'sm="RR"') for studies with a zero cell
          count.

    warn: A logical indicating whether the addition of 'incr' to
          studies with zero cell frequencies should result in a
          warning.

_D_e_t_a_i_l_s:

     Treatment estimates and standard errors are calculated for each
     study. For studies with a zero cell count, by default, 0.5 is
     added to all cell frequencies of these studies. Treatment
     estimates and standard errors are only calculated for studies with
     zero or all events in both groups if 'allstudies' is 'TRUE'.

     Both fixed and random effects estimates are calculated. If
     'method' is '"MH"' (default), the Mantel-Haenszel method is used
     to calculate the fixed effects estimate; if 'method' is
     '"Inverse"', inverse variance weighting is used for pooling;
     finally, if 'method' is '"Peto"', the Peto method is used for
     pooling. The DerSimonian-Laird estimate is used in the random
     effects model.

     For the Mantel-Haenszel method, by default (if 'MH.exact' is
     FALSE), 0.5 is added to all cell frequencies of a study with a
     zero cell count in the calculation of the pooled estimate. This
     approach is also used in other software, e.g. RevMan 4.1 and the
     Stata procedure metan. According to Fleiss (in Cooper & Hedges,
     1994), there is no need to add 0.5 to a cell frequency of zero to
     calculate the Mantel-Haenszel estimate and he advocates the exact
     method ('MH.exact'=TRUE). Note, the estimate based on the exact
     method is not defined if the number of events is zero in all
     studies either in the experimental or control group.

_V_a_l_u_e:

     An object of class 'c("metabin", "meta")' with corresponding
     'print', 'summary', 'plot' function. The object is a list
     containing the following components: 

event.e, n.e, event.c, n.c, studlab,: 

sm, method, incr, allincr, addincr, : As defined above.

allstudies, MH.exact, RR.cochrane, warn: 

TE, seTE: Estimated treatment effect and standard error of individual
          studies.

w.fixed, w.random: Weight of individual studies (in fixed and random
          effects model).

TE.fixed, seTE.fixed: Estimated overall treatment effect and standard
          error (fixed effect model).

TE.random, seTE.random: Estimated overall treatment effect and standard
          error (random effects model).

       k: Number of studies combined in meta-analysis.

       Q: Heterogeneity statistic Q.

     tau: Square-root of between-study variance (moment estimator of
          DerSimonian-Laird).

   Q.CMH: Cochrane-Mantel-Haenszel heterogeneity statistic.

  sparse: Logical flag indicating if any study included in
          meta-analysis has any zero cell frequencies.

    call: Function call.

_A_u_t_h_o_r(_s):

     Guido Schwarzer sc@imbi.uni-freiburg.de

_R_e_f_e_r_e_n_c_e_s:

     Cooper H & Hedges LV (1994), _The Handbook of Research Synthesis_.
     Newbury Park, CA: Russell Sage Foundation.

     DerSimonian R & Laird N (1986), Meta-analysis in clinical trials.
     _Controlled Clinical Trials_, *7*, 177-188.

     Fleiss JL (1993), The statistical basis of meta-analysis.
     _Statistical Methods in Medical Research_, *2*, 121-145.

     Greenland S & Robins JM (1985), Estimation of a common effect
     parameter from sparse follow-up data. _Biometrics_, *41*, 55-68.

     _Review Manager (RevMan)_ [Computer program]. Version 4.1 for
     Windows. Oxford, England: The Cochrane Collaboration, 2000.

     StataCorp. 2001. _Stata Statistical Software: Release 7.0_.
     College Station, TX: Stata Corporation.

_S_e_e _A_l_s_o:

     'funnel', 'metabias', 'metacont', 'metagen', 'print.meta'

_E_x_a_m_p_l_e_s:

     metabin(10, 20, 15, 20, sm="OR")

     ##
     ## Different results:
     ##
     metabin(0, 10, 0, 10, sm="OR")
     metabin(0, 10, 0, 10, sm="OR", allstudies=TRUE)

     data(Olkin95)

     meta1 <- metabin(event.e, n.e, event.c, n.c,
                      data=Olkin95, subset=c(41,47,51,59),
                      sm="RR", meth="I")
     summary(meta1)
     funnel(meta1)

     meta2 <- metabin(event.e, n.e, event.c, n.c,
                      data=Olkin95, subset=Olkin95$year<1970,
                      sm="RR", meth="I")
     summary(meta2)

