structure(list(Estimate = c(0.052, 0.033, -0.055, 0.046, 0.077, 
0.045, -0.038, 0.034, 0.031, 0.05, 0.123, 0.189, 0.118, 0.012, 
-0.02, 0.037, 0.006, 0.002, 0.019, 0.102, 0.125, 0.211, 0.216, 
0.222, 0.209, 0.32, 0.291, 0.226, 0.231, 0.196, 0.034, 0.024, 
0.074, 0.093, 0.189, 0.148, 0.056, 0.074, 0.061, -0.061, -0.122, 
-0.074, -0.124, -0.117, -0.096, -0.218, -0.173, -0.139, -0.175, 
-0.121, -0.21, -0.094, -0.03, 0.036, 0.043), StdErr = c(0.156, 
0.156, 0.151, 0.196, 0.202, 0.204, 0.215, 0.209, 0.191, 0.179, 
0.173, 0.178, 0.175, 0.186, 0.166, 0.176, 0.191, 0.202, 0.2, 
0.196, 0.195, 0.201, 0.204, 0.201, 0.204, 0.202, 0.192, 0.187, 
0.194, 0.189, 0.211, 0.211, 0.204, 0.214, 0.207, 0.213, 0.212, 
0.193, 0.199, 0.208, 0.212, 0.2, 0.184, 0.191, 0.186, 0.174, 
0.174, 0.176, 0.209, 0.221, 0.213, 0.212, 0.216, 0.221, 0.219
), Statistic = c(0.334, 0.21, -0.366, 0.233, 0.382, 0.221, -0.175, 
0.16, 0.16, 0.281, 0.707, 1.063, 0.672, 0.067, -0.122, 0.211, 
0.033, 0.008, 0.095, 0.522, 0.641, 1.05, 1.057, 1.105, 1.024, 
1.588, 1.519, 1.209, 1.191, 1.041, 0.16, 0.112, 0.364, 0.432, 
0.913, 0.696, 0.266, 0.383, 0.309, -0.296, -0.578, -0.37, -0.676, 
-0.614, -0.514, -1.248, -0.993, -0.792, -0.84, -0.55, -0.987, 
-0.443, -0.141, 0.163, 0.198), Prob = c(0.738, 0.834, 0.715, 
0.816, 0.703, 0.825, 0.861, 0.873, 0.873, 0.779, 0.48, 0.288, 
0.501, 0.947, 0.903, 0.833, 0.974, 0.994, 0.925, 0.602, 0.522, 
0.294, 0.29, 0.269, 0.306, 0.112, 0.129, 0.227, 0.234, 0.298, 
0.873, 0.911, 0.716, 0.665, 0.361, 0.486, 0.79, 0.702, 0.757, 
0.767, 0.563, 0.711, 0.499, 0.539, 0.607, 0.212, 0.321, 0.429, 
0.401, 0.582, 0.324, 0.658, 0.888, 0.871, 0.843), DF = c(NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA), Time = c(15500, 15600, 15700, 15800, 
15900, 16000, 16100, 16200, 16300, 16400, 16500, 16600, 16700, 
16800, 16900, 17000, 17100, 17200, 17300, 17400, 17500, 17600, 
17700, 17800, 17900, 18000, 18100, 18200, 18300, 18400, 18500, 
18600, 18700, 18800, 18900, 19000, 19100, 19200, 19300, 19400, 
19500, 19600, 19700, 19800, 19900, 20000, 20100, 20200, 20300, 
20400, 20500, 20600, 20700, 20800, 20900), CritStatisticPos = c(1.96, 
1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 
1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 
1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 
1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 
1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96, 1.96), 
    CritStatisticNeg = c(-1.96, -1.96, -1.96, -1.96, -1.96, -1.96, 
    -1.96, -1.96, -1.96, -1.96, -1.96, -1.96, -1.96, -1.96, -1.96, 
    -1.96, -1.96, -1.96, -1.96, -1.96, -1.96, -1.96, -1.96, -1.96, 
    -1.96, -1.96, -1.96, -1.96, -1.96, -1.96, -1.96, -1.96, -1.96, 
    -1.96, -1.96, -1.96, -1.96, -1.96, -1.96, -1.96, -1.96, -1.96, 
    -1.96, -1.96, -1.96, -1.96, -1.96, -1.96, -1.96, -1.96, -1.96, 
    -1.96, -1.96, -1.96, -1.96), PositiveRuns = c(NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), NegativeRuns = c(NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_
    )), .Names = c("Estimate", "StdErr", "Statistic", "Prob", 
"DF", "Time", "CritStatisticPos", "CritStatisticNeg", "PositiveRuns", 
"NegativeRuns"), eyetrackingR = structure(list(data_options = structure(list(
    participant_column = "ParticipantName", trackloss_column = "TrackLoss", 
    time_column = "TimeFromTrialOnset", trial_column = "Trial", 
    item_columns = NULL, aoi_columns = c("Animate", "Inanimate"
    ), treat_non_aoi_looks_as_missing = TRUE), .Names = c("participant_column", 
"trackloss_column", "time_column", "trial_column", "item_columns", 
"aoi_columns", "treat_non_aoi_looks_as_missing")), summarized_by = "ParticipantName", 
    time_bin_size = 100, formula = Prop ~ Sex * Target + (1 | 
        ParticipantName), p_adjust_method = "none", alpha = 0.05, 
    threshold = NULL, test = "lmer", predictor = "SexM:TargetInanimate", 
    positive_runs = list(), negative_runs = list()), .Names = c("data_options", 
"summarized_by", "time_bin_size", "formula", "p_adjust_method", 
"alpha", "threshold", "test", "predictor", "positive_runs", "negative_runs"
)), row.names = c(NA, 55L), class = c("bin_analysis", "data.frame"
))
